EcoliWiki - User contributions [en]

Help:Genetic nomenclature

2009-12-16T22:30:36Z

Jdime: /* Gene Products */

Genetic nomenclature for ''E. coli'' has evolved since the first formal proposal in 1966 by Demerec et al.<ref>PMID:5961488</ref> The [http://jb.asm.org/misc/ifora.shtml Instructions to Authors for the ''Journal of Bacteriology''] is considered to be an authoritative source for the most recent version of the genetic nomenclature guidelines, along with the nomenclature guide from ''Trends in Genetics''.
==Gene names==
The genetic nomenclature uses gene and locus interchangeably. A gene is named by a three letter italicized lowercase locus mnemonic, such as ''lac'' for lactose, ''trp'' for tryptophan, or ''rpo'' for RNA polymerase. Different genes with the same mnemonic are distinguished by the addition of an uppercase italicized letter, e.g. ''lacZ'', ''lacY'', and ''lacZ'' are the genes of the ''lac'' operon. The three letter mnemonic does not mean that genes with the same designator necessarily map close to one another. However, some genes were named based on proximity to other genes. It was later determined that the function of these were not closely coupled. Thus, similar gene names are not a substitute for functional annotations.

The nomenclature is somewhat inconsitent, for historical reasons, in how cis-elements in the DNA are described. For example, the major origin of replication is ''oriC'', while sites related to the termination of replication include ''RhsA'', ''RhsB'', ''RhsC'', ''RhsD'', ''RhsE'' ('''R'''ecombination '''h'''ot '''s'''pot), ''TerA'', ''TerB'', ''TerC'', ''TerD'', ''TerE'', and ''TerF'' ('''Ter'''minus), where the first letter is capitalized. Transcriptional control elements are to be designated with a lower case letter following a nearby locus, e.g. ''lacZp''. However, it is not unusual to see ''lacP'', ''lacp'' or Plac in the literature (Demerec refers to ''lacO''). Subscripts and superscripts in general are problematic for keeping the data in computer-friendly form.

In some cases, older names refer to a locus that was not resolved into separate genes when the name was given. For example, ''malA'' and ''malB'' refer to two clusters of ''mal'' (maltose) genes that map at 76.4 and 91.5 minutes, respectively. The ''malA'' cluster includes ''malT'', ''malP'' and ''malQ'', while ''malB'' includes ''malE'', ''malF'', ''malG'', ''malK'', ''lamB'', and ''malM''.

===''y'' genes===
Traditional gene names derive from a phenotype mnemonic, or from the identification of a gene based on the protein or RNA product it makes. Thus, ''lac'' refers to genes that are needed for growth on lactose as a sole carbon source, while ''ssrA'' is for "small stable RNA". With genomics, many genes of unknown function were identified as open reading frames with computationally identified. These have been given names like ''ybbN'' where ''y'' indicates a gene of unknown function, and the next two letters indicate the position of the gene on the standard map of ''E. coli K-12'' strain [[MG1655]]. For y gene names, a=0, b=1, c=2, d=3, e=4, f=5, g=6, h=7, i=8, and j=9. Thus, ''ybbN'' is a gene of unknown function that maps at 11 minutes. As with traditional loci, the uppercase letter distinguishes ''ybbN'' from [http://dimer.tamu.edu/cgi-bin/gb/gbrowse/ecoli/?q=MG1655:515649..518503 other genes in the region]. The numbers recycle when more than 26 genes are found in a region<ref>PMID:9729612</ref>.
{|{{Prettytable}} align = 'left'
|-
! digit || letter || overflow letter
|-
|0 || a || k
|-
|1 || b || l
|-
|2 || c || m
|-
|3 || d || n
|-
|4 || e || o
|-
|5 || f || p
|-
|6 || g || q
|-
|7 || h || r
|-
|8 || i || s
|-
|9 || j || t
|}
Thus, ''ykgE'' is a gene of unknown function that [http://dimer.tamu.edu/cgi-bin/gb/gbrowse/ecoli/?q=MG1655:319832..322551 maps at 06 minutes] on the ''E. coli'' genetic map. Large clusters of ''y'' genes are found in cryptic prophage genomes that were discovered during genome sequencing. The ''y'' gene names are not reused if a gene is renamed when its function is assigned, or when a gene name is retired because the ORF has been determined to be not a coding sequence, or when two ''y'' genes are fused by corrections in the DNA sequence.

===z loci===
A similar notation is used to designate loci that are only known by map location. In this case, a ''z'' is used as the first letter and the next two letters describe the coordinates. This is seen most often in designating the site of a transposon insertions, as in the mapping collection from [http://www.pubmedcentral.gov/articlerender.fcgi?artid=372715 Singer et al (1989)].

===Standard names and synonyms===
Standard gene names are currently managed by the [[E. coli Genetic Stock Center (CGSC)]] and can be found on a variety of [[:Category:E. coli Databases|''E. coli'' database websites]]. Many genes have multiple names, or synonyms. This can occur when a gene was given different names based on different alleles that were only later shown to be allelic, or when ''y'' genes are renamed, or when people publish new gene names without consulting the standard names and reviewers and editors don't catch it. Databases have to keep track of synonyms to help find all of the relevant literature for a gene.

In some cases, the synonyms are still widely used.
====sup "genes"====
The mnemonic ''sup'' was used extensively for '''sup'''pressor, to indicate genes that, when mutated, suppress the phenotypes of mutations in other genes. Most, but not all, of the ''sup'' loci in ''E. coli'' are mutations that create [[Nonsense suppressor|nonsense suppressor]] tRNAs. These have been given different standard names, but the ''sup'' names are still used by ''E. coli'' biologists. These names are useful because they are shorthand for particular alleles. The same tRNA gene can often mutate to some combination of amber (UAG), ochre (UAA), or opal (UGA) suppressors.

====Other commonly used synonyms====
Strain descriptions in the literature or in laboratory strain lists often use ''str'' to indicate an allele of ''rpsL'' that confers resistance to streptomycin.

===Conflicts===
Databases also need to deal with situations where the same gene name has been used by different groups to designate different genes. Although the standard names are unique, the literature has instances of the same name referring to different genes.

==Alleles==
In general the wild-type allele is implicit in the genotype description of a strain; only genes with mutations are listed. Allele designators are used to specify the mutations in a strain; for example, ''araD139'' is a mutation in ''araD'' found in many commonly used laboratory strains. In some cases, noninteger allele designations are used, as in ''lacI''q<ref>PMID:3015603</ref> or ''nusAcs10''<ref>PMID:9139668</ref>. Under the ''J. Bact'' guidelines, qualifiers indicating temperature-sensitive, cold-sensitive, or hybrid alleles should be inicated in parentheses after the allele number. Using these rules ''nusAcs10'' should probably be ''nusA10(Cs)''. However, many variants can be found in the literature. For example, ''argE''(Am), ''argE''-am, and ''argE''am all indicate amber mutations in the ''argE'' gene. Variations in usage and capitalization can make it difficult to extract instances of the same alleles by text searching. This kind of problem is not unique to ''E. coli''<ref>PMID:15214961</ref>.

After gene sequences became available and identifying the sequence changes for mutant alleles became the norm, alleles have been described based on the changes created in the sequence of the encoded polypeptide. Some papers expressed this as two single letter amino acid codes followed by a position in the protein, but it is now more common to use two single letter amino acids separated by the position. Thus, QL44 and Q44L would both indicate a change from a glutamine to a leucine at position 44 of the polypeptide encoded by the gene of interest.

In principle, allele numbers should be registered with the [[CGSC]], but many unregistered mutant alleles are in the literature.
===Deletions, Insertions, and Fusions===
Special notation is used for mutations that are not single base substitutions.

Deletions are indicted as Δ, <nowiki>[Delta]</nowiki> or spelled out as Delta (the last is more friendly to computer searching; the <nowiki>[Delta]</nowiki> version is particularly bad for wikis since it must be embedded in <nowiki><nowiki></nowiki> tags), as in Δ(''ara-leu'')7696 or Δ(''lac'')X74. This nomenclature does not specify which genes are missing in the deletion; one must find additional information about the specific allele.

Insertions are indicated by ::, as in ''pyrC103::Tn10'' to indicate a Tn10 insertion into the ''pyrC'' gene. Insertions that are linked to, but not in a nearby gene are sometimes connected by a dash, as in ''proC''-Tn10.

Gene fusions are powerful tools for a variety of purposes <ref>PMID:3005818</ref>. These are usually either noted with a dash, as in ''trp-lac'' or ''lamB-lacZ''. Sometimes the fusion is generated via an insertion vector, in which case the insertion designation may be used.

==Episomes and mobile genetic elements==
Episomes include plasmids, like F, and integrated elements that have a free-living stage in their life cycle, such as prophage. These are indicated in various ways. For example, a strain that is [[W3110]] with F'128 might be written W3110/F'128 or W3110(F'128). Lysogens are written with the integrated phage in parentheses, as in C600(λ), not C600 ''att''λ::λ. [[F']]s and [[specialized transducing phage]] carry chromosomal genes. In this case the wt gene is often indicated. While this should be written as, for example, F'128 ''proAB''+''lac''+, this is often just written as F'128 ''pro lac''.

==Phenotypes==
Phenotypes are given as nonitalicized mnemonics beginning with an uppercase letter. A mutant that is unable to use lactose as the sole carbon source would be designated as having a Lac or Lac- phenotype. Superscripts are also used to clarify specific phenotypes such as sensitivity or resistance; a tetracycline-resistant strain is Tetr, while a tetracycline-sensitive strain is Tets. Superscripts are also used for conditional phenotypes such as ts (temperature-sensitive) or cs (cold-sensitive). A superscript zero is sometimes used to designate a strain that does not contain nonsense suppressors: Sup0.

==Gene Products==
When referring to the gene product the mnemonic is first-letter capitalised and not italicized (e.g. DnaA refers to the protein coded by the ''dnaA'' gene).

==References==
<references />

[[Category:Help|{{PAGENAME}}]]

Help:Genetic nomenclature

2009-12-16T22:29:08Z

Jdime: /* Gene Products */

Genetic nomenclature for ''E. coli'' has evolved since the first formal proposal in 1966 by Demerec et al.<ref>PMID:5961488</ref> The [http://jb.asm.org/misc/ifora.shtml Instructions to Authors for the ''Journal of Bacteriology''] is considered to be an authoritative source for the most recent version of the genetic nomenclature guidelines, along with the nomenclature guide from ''Trends in Genetics''.
==Gene names==
The genetic nomenclature uses gene and locus interchangeably. A gene is named by a three letter italicized lowercase locus mnemonic, such as ''lac'' for lactose, ''trp'' for tryptophan, or ''rpo'' for RNA polymerase. Different genes with the same mnemonic are distinguished by the addition of an uppercase italicized letter, e.g. ''lacZ'', ''lacY'', and ''lacZ'' are the genes of the ''lac'' operon. The three letter mnemonic does not mean that genes with the same designator necessarily map close to one another. However, some genes were named based on proximity to other genes. It was later determined that the function of these were not closely coupled. Thus, similar gene names are not a substitute for functional annotations.

The nomenclature is somewhat inconsitent, for historical reasons, in how cis-elements in the DNA are described. For example, the major origin of replication is ''oriC'', while sites related to the termination of replication include ''RhsA'', ''RhsB'', ''RhsC'', ''RhsD'', ''RhsE'' ('''R'''ecombination '''h'''ot '''s'''pot), ''TerA'', ''TerB'', ''TerC'', ''TerD'', ''TerE'', and ''TerF'' ('''Ter'''minus), where the first letter is capitalized. Transcriptional control elements are to be designated with a lower case letter following a nearby locus, e.g. ''lacZp''. However, it is not unusual to see ''lacP'', ''lacp'' or Plac in the literature (Demerec refers to ''lacO''). Subscripts and superscripts in general are problematic for keeping the data in computer-friendly form.

In some cases, older names refer to a locus that was not resolved into separate genes when the name was given. For example, ''malA'' and ''malB'' refer to two clusters of ''mal'' (maltose) genes that map at 76.4 and 91.5 minutes, respectively. The ''malA'' cluster includes ''malT'', ''malP'' and ''malQ'', while ''malB'' includes ''malE'', ''malF'', ''malG'', ''malK'', ''lamB'', and ''malM''.

===''y'' genes===
Traditional gene names derive from a phenotype mnemonic, or from the identification of a gene based on the protein or RNA product it makes. Thus, ''lac'' refers to genes that are needed for growth on lactose as a sole carbon source, while ''ssrA'' is for "small stable RNA". With genomics, many genes of unknown function were identified as open reading frames with computationally identified. These have been given names like ''ybbN'' where ''y'' indicates a gene of unknown function, and the next two letters indicate the position of the gene on the standard map of ''E. coli K-12'' strain [[MG1655]]. For y gene names, a=0, b=1, c=2, d=3, e=4, f=5, g=6, h=7, i=8, and j=9. Thus, ''ybbN'' is a gene of unknown function that maps at 11 minutes. As with traditional loci, the uppercase letter distinguishes ''ybbN'' from [http://dimer.tamu.edu/cgi-bin/gb/gbrowse/ecoli/?q=MG1655:515649..518503 other genes in the region]. The numbers recycle when more than 26 genes are found in a region<ref>PMID:9729612</ref>.
{|{{Prettytable}} align = 'left'
|-
! digit || letter || overflow letter
|-
|0 || a || k
|-
|1 || b || l
|-
|2 || c || m
|-
|3 || d || n
|-
|4 || e || o
|-
|5 || f || p
|-
|6 || g || q
|-
|7 || h || r
|-
|8 || i || s
|-
|9 || j || t
|}
Thus, ''ykgE'' is a gene of unknown function that [http://dimer.tamu.edu/cgi-bin/gb/gbrowse/ecoli/?q=MG1655:319832..322551 maps at 06 minutes] on the ''E. coli'' genetic map. Large clusters of ''y'' genes are found in cryptic prophage genomes that were discovered during genome sequencing. The ''y'' gene names are not reused if a gene is renamed when its function is assigned, or when a gene name is retired because the ORF has been determined to be not a coding sequence, or when two ''y'' genes are fused by corrections in the DNA sequence.

===z loci===
A similar notation is used to designate loci that are only known by map location. In this case, a ''z'' is used as the first letter and the next two letters describe the coordinates. This is seen most often in designating the site of a transposon insertions, as in the mapping collection from [http://www.pubmedcentral.gov/articlerender.fcgi?artid=372715 Singer et al (1989)].

===Standard names and synonyms===
Standard gene names are currently managed by the [[E. coli Genetic Stock Center (CGSC)]] and can be found on a variety of [[:Category:E. coli Databases|''E. coli'' database websites]]. Many genes have multiple names, or synonyms. This can occur when a gene was given different names based on different alleles that were only later shown to be allelic, or when ''y'' genes are renamed, or when people publish new gene names without consulting the standard names and reviewers and editors don't catch it. Databases have to keep track of synonyms to help find all of the relevant literature for a gene.

In some cases, the synonyms are still widely used.
====sup "genes"====
The mnemonic ''sup'' was used extensively for '''sup'''pressor, to indicate genes that, when mutated, suppress the phenotypes of mutations in other genes. Most, but not all, of the ''sup'' loci in ''E. coli'' are mutations that create [[Nonsense suppressor|nonsense suppressor]] tRNAs. These have been given different standard names, but the ''sup'' names are still used by ''E. coli'' biologists. These names are useful because they are shorthand for particular alleles. The same tRNA gene can often mutate to some combination of amber (UAG), ochre (UAA), or opal (UGA) suppressors.

====Other commonly used synonyms====
Strain descriptions in the literature or in laboratory strain lists often use ''str'' to indicate an allele of ''rpsL'' that confers resistance to streptomycin.

===Conflicts===
Databases also need to deal with situations where the same gene name has been used by different groups to designate different genes. Although the standard names are unique, the literature has instances of the same name referring to different genes.

==Alleles==
In general the wild-type allele is implicit in the genotype description of a strain; only genes with mutations are listed. Allele designators are used to specify the mutations in a strain; for example, ''araD139'' is a mutation in ''araD'' found in many commonly used laboratory strains. In some cases, noninteger allele designations are used, as in ''lacI''q<ref>PMID:3015603</ref> or ''nusAcs10''<ref>PMID:9139668</ref>. Under the ''J. Bact'' guidelines, qualifiers indicating temperature-sensitive, cold-sensitive, or hybrid alleles should be inicated in parentheses after the allele number. Using these rules ''nusAcs10'' should probably be ''nusA10(Cs)''. However, many variants can be found in the literature. For example, ''argE''(Am), ''argE''-am, and ''argE''am all indicate amber mutations in the ''argE'' gene. Variations in usage and capitalization can make it difficult to extract instances of the same alleles by text searching. This kind of problem is not unique to ''E. coli''<ref>PMID:15214961</ref>.

After gene sequences became available and identifying the sequence changes for mutant alleles became the norm, alleles have been described based on the changes created in the sequence of the encoded polypeptide. Some papers expressed this as two single letter amino acid codes followed by a position in the protein, but it is now more common to use two single letter amino acids separated by the position. Thus, QL44 and Q44L would both indicate a change from a glutamine to a leucine at position 44 of the polypeptide encoded by the gene of interest.

In principle, allele numbers should be registered with the [[CGSC]], but many unregistered mutant alleles are in the literature.
===Deletions, Insertions, and Fusions===
Special notation is used for mutations that are not single base substitutions.

Deletions are indicted as Δ, <nowiki>[Delta]</nowiki> or spelled out as Delta (the last is more friendly to computer searching; the <nowiki>[Delta]</nowiki> version is particularly bad for wikis since it must be embedded in <nowiki><nowiki></nowiki> tags), as in Δ(''ara-leu'')7696 or Δ(''lac'')X74. This nomenclature does not specify which genes are missing in the deletion; one must find additional information about the specific allele.

Insertions are indicated by ::, as in ''pyrC103::Tn10'' to indicate a Tn10 insertion into the ''pyrC'' gene. Insertions that are linked to, but not in a nearby gene are sometimes connected by a dash, as in ''proC''-Tn10.

Gene fusions are powerful tools for a variety of purposes <ref>PMID:3005818</ref>. These are usually either noted with a dash, as in ''trp-lac'' or ''lamB-lacZ''. Sometimes the fusion is generated via an insertion vector, in which case the insertion designation may be used.

==Episomes and mobile genetic elements==
Episomes include plasmids, like F, and integrated elements that have a free-living stage in their life cycle, such as prophage. These are indicated in various ways. For example, a strain that is [[W3110]] with F'128 might be written W3110/F'128 or W3110(F'128). Lysogens are written with the integrated phage in parentheses, as in C600(λ), not C600 ''att''λ::λ. [[F']]s and [[specialized transducing phage]] carry chromosomal genes. In this case the wt gene is often indicated. While this should be written as, for example, F'128 ''proAB''+''lac''+, this is often just written as F'128 ''pro lac''.

==Phenotypes==
Phenotypes are given as nonitalicized mnemonics beginning with an uppercase letter. A mutant that is unable to use lactose as the sole carbon source would be designated as having a Lac or Lac- phenotype. Superscripts are also used to clarify specific phenotypes such as sensitivity or resistance; a tetracycline-resistant strain is Tetr, while a tetracycline-sensitive strain is Tets. Superscripts are also used for conditional phenotypes such as ts (temperature-sensitive) or cs (cold-sensitive). A superscript zero is sometimes used to designate a strain that does not contain nonsense suppressors: Sup0.

==Gene Products==
When referring to the gene product the mnemonic is first-letter capitalised and not italicized (e.g. DnaA - the protein produced by the dnaA gene, or LeuA- - the phenotype of a leuA mutant). Gene Products nomenclature is similar to that referring to phenotype.

==References==
<references />

[[Category:Help|{{PAGENAME}}]]

mtgA:Quickview

2009-10-07T19:43:49Z

Jdime: /* Notes */

{{#css:Suppresslinks.css}}<css>{{:Suppresslinks.css}}</css>
<noinclude>{{TabsTop}}
{{Tab On|Quickview|mtgA}}{{Tab|Gene|mtgA}}{{Tab|Gene Product(s)|mtgA}}{{Tab|Expression|mtgA}}{{Tab|Evolution|mtgA}}{{Tab|On One Page|mtgA}}{{TabsBottom}}
{|
|- style="background-color:white; border:solid 2px #CCFFFF; text-align:center; white-space: nowrap;"
|{{Sub}}[[#References| References]]
|{{Sub}}[[Talk:{{PAGENAMEE}}| Suggestions]]
|}
</noinclude>
<protect>
{{Quickview_table_help}}
{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;"

|-
!align=left {{table_heading_style}} |Standard Name
||
''mtgA''
|-
!align=left {{table_heading_style}} |Gene Synonym(s)
||
''ECK3197, b3208, JW3175, yrbM, mgt''<ref name='LIB:Riley_2006'/>
|-
!align=left {{table_heading_style}} |Product Desc.
||
biosynthetic peptidoglycan transglycosylase<ref name='LIB:EcoCyc10.6'/><ref name='LIB:EcoCyc11.1'/>

Monofunctional peptidoglycan glycosyltransferase; monofunctional biosynthetic peptidoglycan transglycosylase; GTase; TGase<ref name='LIB:EcoGene'/>
|-
!align=left {{table_heading_style}} |Product Synonyms(s)
||
biosynthetic peptidoglycan transglycosylase<ref name='LIB:Riley_2006'/>, B3208<ref name='LIB:EcoCyc10.6'/><ref name='LIB:Riley_2006'/>, Mgt<ref name='LIB:EcoCyc10.6'/><ref name='LIB:Riley_2006'/>, YrbM<ref name='LIB:EcoCyc10.6'/><ref name='LIB:Riley_2006'/>, MtgA<ref name='LIB:EcoCyc10.6'/><ref name='LIB:Riley_2006'/>
|-
!align=left {{table_heading_style}} |Knock-Out Phenotype
||

|-
!align=left {{table_heading_style}} |Regulation/Expression
||
transcription unit(s): [[:Category:Txn_unit:mtgA|mtgA]]<ref name='LIB:EcoCyc10.6'/>
|-
!align=left {{table_heading_style}} |Regulation/Activity
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=bc145ea147f7e36caf09c1bfeed4ee9d.8156.L49aeed537a6c4&page=8156&pagename={{FULLPAGENAMEE}}&type=1&template=New_Quickview_Table edit table] ||
|}
</protect>
{{Quickview_table_help}}
<protect></protect>
===Notes===
{{BacktoTop}}

MtgA has flavomycin-resistant peptidoglycan synthesis activity (Di Berardino, 1996 <ref name=PMID:8772200/>; Derouaux, 2007). mtgA is a non-essential gene (Schiffer, 1999). MtgA localizes to the division site and interacts with FtsW, FtsN, and FtsI in mcrA(Ts) mrcB- strains, indicating a role for MtgA in peptidoglycan synthesis related to the cell cycle (Derouaux, 2007). The use of the term transglycolase is ambiguous as it can describe both lytic and synthetic peptidoglycan activities, therefore glycosyltransferase is preferred (Di Berardino, 1996). MtgA lacks a penicillin binding domain and therefore is penicillin-insensitive. MtgA is a membrane-bound periplasmic enzyme that has an uncleaved signal anchor (Di Berardino, 1996). MtgA may be the glycan polymerase characterized by Hara (1984), although it has an apparent MW larger than MtgA (Di Berardino, 1996).<ref name='LIB:EcoGene'/>

<noinclude>

==References==
{{BacktoTop}}

<references/>
</noinclude>

eNet

2009-07-16T17:20:40Z

Jdime: /* Usage examples */

{{Pagetop}} 
{{See|Help:Databases|databases}}
[[Category:Databases]]
<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
[http://www.utoronto.ca/emililab/ Emili Lab] @ University of Toronto, and [http://popolvuh.wlu.ca/ Moreno-Hagelsieb Lab] @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
[http://www.lusara.org/jdime/ Javier Diaz] (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009) <ref name='PMID:19402753'/>
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/] <ref name='PMID:19402753'/>.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
The following options are available for searching and browsing genes/proteins at eNet: 
-Gene Name / B-numbers (Blattner-number) 
-Gene Product (current annotation) 
-Keyword 
-Multiple Gene Names / B-numbers (to work in semi-batch mode) 
-Batch Mode 
-Project (according to finished projects at the Emili lab) 
-Prediction profile of a gene (according function predictions by Hu. et al 2009) 
-Prediction profile for a specific functional category (all genes predicted to belong a functional category by Hu et al 2009) 
-Download data (Supplementary material in text and PSI-ML formats, including function predictions, networks, clusters, etc) 
-Gene Name / B-numbers (Blattner-number) 
See eNet 'Help' section for details

----

===Usage examples===
See [http://ecid.bioinfo.cnio.es/ eNet] 'Help' section for examples

==Other sites with related content {{HelpIcon|Help:Databases}}==
EciD [http://ecoliwiki.net/colipedia/index.php/EciD EcoliWiki page] [http://ecid.bioinfo.cnio.es/ EciD webpage] 
String [http://string.embl.de/ String webpage]

==Technology==
===Web Services/API===

==Discussion==

==References==
<references/>

==External Links==
eNet: http://ecoli.med.utoronto.ca/ 
Emili lab @ University of Toronto: http://www.utoronto.ca/emililab/ 
Moreno-Hagelsieb lab @ Wilfrid Laurier University: http://popolvuh.wlu.ca/
===Discussion of {{PAGENAME}} on other websites===
Featured in '''EcoliHub''' Release 1.6.0: http://www.ecolihub.org/ 
Research highlight in '''Nature Methods''' (2009): http://www.nature.com/nmeth/journal/v6/n6/full/nmeth0609-402b.html

eNet

2009-07-15T17:54:16Z

Jdime: /* Other sites with related content {{HelpIcon|Help:Databases}} */

{{Pagetop}} 
{{See|Help:Databases|databases}}
[[Category:Databases]]
<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
[http://www.utoronto.ca/emililab/ Emili Lab] @ University of Toronto, and [http://popolvuh.wlu.ca/ Moreno-Hagelsieb Lab] @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
[http://www.lusara.org/jdime/ Javier Diaz] (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009) <ref name='PMID:19402753'/>
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/] <ref name='PMID:19402753'/>.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
The following options are available for searching and browsing genes/proteins at eNet: 
-Gene Name / B-numbers (Blattner-number) 
-Gene Product (current annotation) 
-Keyword 
-Multiple Gene Names / B-numbers (to work in semi-batch mode) 
-Batch Mode 
-Project (according to finished projects at the Emili lab) 
-Prediction profile of a gene (according function predictions by Hu. et al 2009) 
-Prediction profile for a specific functional category (all genes predicted to belong a functional category by Hu et al 2009) 
-Download data (Supplementary material in text and PSI-ML formats, including function predictions, networks, clusters, etc) 
-Gene Name / B-numbers (Blattner-number) 
See eNet 'Help' section for details

----

===Usage examples===
See eNet 'Help' section for examples

==Other sites with related content {{HelpIcon|Help:Databases}}==
EciD [http://ecoliwiki.net/colipedia/index.php/EciD EcoliWiki page] [http://ecid.bioinfo.cnio.es/ EciD webpage] 
String [http://string.embl.de/ String webpage]

==Technology==
===Web Services/API===

==Discussion==

==References==
<references/>

==External Links==
eNet: http://ecoli.med.utoronto.ca/ 
Emili lab @ University of Toronto: http://www.utoronto.ca/emililab/ 
Moreno-Hagelsieb lab @ Wilfrid Laurier University: http://popolvuh.wlu.ca/
===Discussion of {{PAGENAME}} on other websites===
Featured in '''EcoliHub''' Release 1.6.0: http://www.ecolihub.org/ 
Research highlight in '''Nature Methods''' (2009): http://www.nature.com/nmeth/journal/v6/n6/full/nmeth0609-402b.html

EciD

2009-07-15T17:53:32Z

Jdime: /* Other sites with related content {{HelpIcon|Help:Databases}} */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
[http://ecid.bioinfo.cnio.es/ EciD]
|-
!align=left {{table heading style}} |What:
||
For exploring the sizeable amount of protein interaction-related data available for Escherichia coli
|-
!align=left {{table heading style}} |Who:
||
Alfonso Valencia
|-
!align=left {{table heading style}} |Updates:
||

|-
!align=left {{table heading style}} |Upcoming events:
||

|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164861.X4a439de917522&page=164861&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About {{PAGENAME}}==
[[Image:Ecid_home.jpg|300px|thumb|right|Home Page]]
''Add general information here''
[{{{1|link}}} {{PAGENAME}}] is...<ref name='PMID:19004873'/>

==Content==

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==
eNet [http://ecoliwiki.net/colipedia/index.php/eNet EcoliWiki page] [http://ecoli.med.utoronto.ca/ eNet webpage] 
String [http://string.embl.de/ String webpage]

==Technology==
===Web Services/API===

==Discussion==

==References==
{{BacktoTop}}
{{RefHelp}}
<references />

==External Links==
[{{{1|link}}} {{PAGENAME}}] URL:{{{1|link}}}

===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-07-15T17:52:10Z

Jdime: /* Other sites with related content {{HelpIcon|Help:Databases}} */

{{Pagetop}} 
{{See|Help:Databases|databases}}
[[Category:Databases]]
<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
[http://www.utoronto.ca/emililab/ Emili Lab] @ University of Toronto, and [http://popolvuh.wlu.ca/ Moreno-Hagelsieb Lab] @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
[http://www.lusara.org/jdime/ Javier Diaz] (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009) <ref name='PMID:19402753'/>
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/] <ref name='PMID:19402753'/>.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
The following options are available for searching and browsing genes/proteins at eNet: 
-Gene Name / B-numbers (Blattner-number) 
-Gene Product (current annotation) 
-Keyword 
-Multiple Gene Names / B-numbers (to work in semi-batch mode) 
-Batch Mode 
-Project (according to finished projects at the Emili lab) 
-Prediction profile of a gene (according function predictions by Hu. et al 2009) 
-Prediction profile for a specific functional category (all genes predicted to belong a functional category by Hu et al 2009) 
-Download data (Supplementary material in text and PSI-ML formats, including function predictions, networks, clusters, etc) 
-Gene Name / B-numbers (Blattner-number) 
See eNet 'Help' section for details

----

===Usage examples===
See eNet 'Help' section for examples

==Other sites with related content {{HelpIcon|Help:Databases}}==
EciD [http://ecoliwiki.net/colipedia/index.php/EciD EcoliWiki page] [http://ecoli.med.utoronto.ca/ eNet webpage] 
String [http://string.embl.de/ String webpage]

==Technology==
===Web Services/API===

==Discussion==

==References==
<references/>

==External Links==
eNet: http://ecoli.med.utoronto.ca/ 
Emili lab @ University of Toronto: http://www.utoronto.ca/emililab/ 
Moreno-Hagelsieb lab @ Wilfrid Laurier University: http://popolvuh.wlu.ca/
===Discussion of {{PAGENAME}} on other websites===
Featured in '''EcoliHub''' Release 1.6.0: http://www.ecolihub.org/ 
Research highlight in '''Nature Methods''' (2009): http://www.nature.com/nmeth/journal/v6/n6/full/nmeth0609-402b.html

eNet

2009-07-15T17:47:50Z

Jdime: /* Other sites with related content {{HelpIcon|Help:Databases}} */

{{Pagetop}} 
{{See|Help:Databases|databases}}
[[Category:Databases]]
<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
[http://www.utoronto.ca/emililab/ Emili Lab] @ University of Toronto, and [http://popolvuh.wlu.ca/ Moreno-Hagelsieb Lab] @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
[http://www.lusara.org/jdime/ Javier Diaz] (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009) <ref name='PMID:19402753'/>
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/] <ref name='PMID:19402753'/>.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
The following options are available for searching and browsing genes/proteins at eNet: 
-Gene Name / B-numbers (Blattner-number) 
-Gene Product (current annotation) 
-Keyword 
-Multiple Gene Names / B-numbers (to work in semi-batch mode) 
-Batch Mode 
-Project (according to finished projects at the Emili lab) 
-Prediction profile of a gene (according function predictions by Hu. et al 2009) 
-Prediction profile for a specific functional category (all genes predicted to belong a functional category by Hu et al 2009) 
-Download data (Supplementary material in text and PSI-ML formats, including function predictions, networks, clusters, etc) 
-Gene Name / B-numbers (Blattner-number) 
See eNet 'Help' section for details

----

===Usage examples===
See eNet 'Help' section for examples

==Other sites with related content {{HelpIcon|Help:Databases}}==
EciD http://ecoliwiki.net/colipedia/index.php/EciD 
String http://string.embl.de/

==Technology==
===Web Services/API===

==Discussion==

==References==
<references/>

==External Links==
eNet: http://ecoli.med.utoronto.ca/ 
Emili lab @ University of Toronto: http://www.utoronto.ca/emililab/ 
Moreno-Hagelsieb lab @ Wilfrid Laurier University: http://popolvuh.wlu.ca/
===Discussion of {{PAGENAME}} on other websites===
Featured in '''EcoliHub''' Release 1.6.0: http://www.ecolihub.org/ 
Research highlight in '''Nature Methods''' (2009): http://www.nature.com/nmeth/journal/v6/n6/full/nmeth0609-402b.html

eNet

2009-07-15T17:45:33Z

Jdime: /* Other sites with related content {{HelpIcon|Help:Databases}} */

{{Pagetop}} 
{{See|Help:Databases|databases}}
[[Category:Databases]]
<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
[http://www.utoronto.ca/emililab/ Emili Lab] @ University of Toronto, and [http://popolvuh.wlu.ca/ Moreno-Hagelsieb Lab] @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
[http://www.lusara.org/jdime/ Javier Diaz] (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009) <ref name='PMID:19402753'/>
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/] <ref name='PMID:19402753'/>.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
The following options are available for searching and browsing genes/proteins at eNet: 
-Gene Name / B-numbers (Blattner-number) 
-Gene Product (current annotation) 
-Keyword 
-Multiple Gene Names / B-numbers (to work in semi-batch mode) 
-Batch Mode 
-Project (according to finished projects at the Emili lab) 
-Prediction profile of a gene (according function predictions by Hu. et al 2009) 
-Prediction profile for a specific functional category (all genes predicted to belong a functional category by Hu et al 2009) 
-Download data (Supplementary material in text and PSI-ML formats, including function predictions, networks, clusters, etc) 
-Gene Name / B-numbers (Blattner-number) 
See eNet 'Help' section for details

----

===Usage examples===
See eNet 'Help' section for examples

==Other sites with related content {{HelpIcon|Help:Databases}}==
EciD http://ecoliwiki.net/colipedia/index.php/EciD
String http://string.embl.de/

==Technology==
===Web Services/API===

==Discussion==

==References==
<references/>

==External Links==
eNet: http://ecoli.med.utoronto.ca/ 
Emili lab @ University of Toronto: http://www.utoronto.ca/emililab/ 
Moreno-Hagelsieb lab @ Wilfrid Laurier University: http://popolvuh.wlu.ca/
===Discussion of {{PAGENAME}} on other websites===
Featured in '''EcoliHub''' Release 1.6.0: http://www.ecolihub.org/ 
Research highlight in '''Nature Methods''' (2009): http://www.nature.com/nmeth/journal/v6/n6/full/nmeth0609-402b.html

eNet

2009-07-15T17:41:28Z

Jdime: /* Using {{PAGENAME}} */

{{Pagetop}} 
{{See|Help:Databases|databases}}
[[Category:Databases]]
<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
[http://www.utoronto.ca/emililab/ Emili Lab] @ University of Toronto, and [http://popolvuh.wlu.ca/ Moreno-Hagelsieb Lab] @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
[http://www.lusara.org/jdime/ Javier Diaz] (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009) <ref name='PMID:19402753'/>
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/] <ref name='PMID:19402753'/>.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
The following options are available for searching and browsing genes/proteins at eNet: 
-Gene Name / B-numbers (Blattner-number) 
-Gene Product (current annotation) 
-Keyword 
-Multiple Gene Names / B-numbers (to work in semi-batch mode) 
-Batch Mode 
-Project (according to finished projects at the Emili lab) 
-Prediction profile of a gene (according function predictions by Hu. et al 2009) 
-Prediction profile for a specific functional category (all genes predicted to belong a functional category by Hu et al 2009) 
-Download data (Supplementary material in text and PSI-ML formats, including function predictions, networks, clusters, etc) 
-Gene Name / B-numbers (Blattner-number) 
See eNet 'Help' section for details

----

===Usage examples===
See eNet 'Help' section for examples

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
<references/>

==External Links==
eNet: http://ecoli.med.utoronto.ca/ 
Emili lab @ University of Toronto: http://www.utoronto.ca/emililab/ 
Moreno-Hagelsieb lab @ Wilfrid Laurier University: http://popolvuh.wlu.ca/
===Discussion of {{PAGENAME}} on other websites===
Featured in '''EcoliHub''' Release 1.6.0: http://www.ecolihub.org/ 
Research highlight in '''Nature Methods''' (2009): http://www.nature.com/nmeth/journal/v6/n6/full/nmeth0609-402b.html

eNet

2009-07-15T17:34:56Z

Jdime: /* Using {{PAGENAME}} */

{{Pagetop}} 
{{See|Help:Databases|databases}}
[[Category:Databases]]
<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
[http://www.utoronto.ca/emililab/ Emili Lab] @ University of Toronto, and [http://popolvuh.wlu.ca/ Moreno-Hagelsieb Lab] @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
[http://www.lusara.org/jdime/ Javier Diaz] (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009) <ref name='PMID:19402753'/>
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/] <ref name='PMID:19402753'/>.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
The following options are available for searching and browsing genes/proteins at eNet:
* Gene Name / B-numbers (Blattner-number)
* Gene Product (current annotation)
* Keyword
* Multiple Gene Names / B-numbers (to work in semi-batch mode)
* Batch Mode
* Project (according to finished projects at the Emili lab)
* Prediction profile of a gene (according function predictions by Hu. et al 2009)
* Prediction profile for a specific functional category (all genes predicted to belong a functional category by Hu et al 2009)
* Download data (Supplementary material in text and PSI-ML formats, including function predictions, physical and functional networks, clusters, etc)

See eNet 'Help' section for details

===Usage examples===
See eNet 'Help' section for examples

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
<references/>

==External Links==
eNet: http://ecoli.med.utoronto.ca/ 
Emili lab @ University of Toronto: http://www.utoronto.ca/emililab/ 
Moreno-Hagelsieb lab @ Wilfrid Laurier University: http://popolvuh.wlu.ca/
===Discussion of {{PAGENAME}} on other websites===
Featured in '''EcoliHub''' Release 1.6.0: http://www.ecolihub.org/ 
Research highlight in '''Nature Methods''' (2009): http://www.nature.com/nmeth/journal/v6/n6/full/nmeth0609-402b.html

eNet

2009-07-01T02:35:03Z

Jdime: /* References */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
[http://www.utoronto.ca/emililab/ Emili Lab] @ University of Toronto, and [http://popolvuh.wlu.ca/ Moreno-Hagelsieb Lab] @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
[http://www.lusara.org/jdime/ Javier Diaz] (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009) <ref name='PMID:19402753'/>
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/] <ref name='PMID:19402753'/>.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
<references/>

==External Links==
eNet: http://ecoli.med.utoronto.ca/ 
Emili lab @ University of Toronto: http://www.utoronto.ca/emililab/ 
Moreno-Hagelsieb lab @ Wilfrid Laurier University: http://popolvuh.wlu.ca/
===Discussion of {{PAGENAME}} on other websites===
Featured in '''EcoliHub''' Release 1.6.0: http://www.ecolihub.org/ 
Research highlight in '''Nature Methods''' (2009): http://www.nature.com/nmeth/journal/v6/n6/full/nmeth0609-402b.html

eNet

2009-07-01T02:29:02Z

Jdime: /* References */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
[http://www.utoronto.ca/emililab/ Emili Lab] @ University of Toronto, and [http://popolvuh.wlu.ca/ Moreno-Hagelsieb Lab] @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
[http://www.lusara.org/jdime/ Javier Diaz] (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009) <ref name='PMID:19402753'/>
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/] <ref name='PMID:19402753'/>.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
[1] Hu P et al. (2009) Global functional atlas of Escherichia coli encompassing previously uncharacterized proteins. PLoS Biol 7: e96 [http://www.ncbi.nlm.nih.gov/sites/entrez?db=pubmed&cmd=search&term=19402753 : PubMed]

==External Links==
eNet: http://ecoli.med.utoronto.ca/ 
Emili lab @ University of Toronto: http://www.utoronto.ca/emililab/ 
Moreno-Hagelsieb lab @ Wilfrid Laurier University: http://popolvuh.wlu.ca/
===Discussion of {{PAGENAME}} on other websites===
Featured in '''EcoliHub''' Release 1.6.0: http://www.ecolihub.org/ 
Research highlight in '''Nature Methods''' (2009): http://www.nature.com/nmeth/journal/v6/n6/full/nmeth0609-402b.html

eNet

2009-06-29T23:25:36Z

Jdime: /* References */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
[http://www.utoronto.ca/emililab/ Emili Lab] @ University of Toronto, and [http://popolvuh.wlu.ca/ Moreno-Hagelsieb Lab] @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
[http://www.lusara.org/jdime/ Javier Diaz] (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009) <ref name='PMID:19402753'/>
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/] <ref name='PMID:19402753'/>.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
<references />

==External Links==
eNet: http://ecoli.med.utoronto.ca/ 
Emili lab @ University of Toronto: http://www.utoronto.ca/emililab/ 
Moreno-Hagelsieb lab @ Wilfrid Laurier University: http://popolvuh.wlu.ca/
===Discussion of {{PAGENAME}} on other websites===
Featured in '''EcoliHub''' Release 1.6.0: http://www.ecolihub.org/ 
Research highlight in '''Nature Methods''' (2009): http://www.nature.com/nmeth/journal/v6/n6/full/nmeth0609-402b.html

eNet

2009-06-29T23:24:30Z

Jdime: /* Discussion of {{PAGENAME}} on other websites */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
[http://www.utoronto.ca/emililab/ Emili Lab] @ University of Toronto, and [http://popolvuh.wlu.ca/ Moreno-Hagelsieb Lab] @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
[http://www.lusara.org/jdime/ Javier Diaz] (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009) <ref name='PMID:19402753'/>
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/] <ref name='PMID:19402753'/>.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
{{RefHelp}}
<references />

==External Links==
eNet: http://ecoli.med.utoronto.ca/ 
Emili lab @ University of Toronto: http://www.utoronto.ca/emililab/ 
Moreno-Hagelsieb lab @ Wilfrid Laurier University: http://popolvuh.wlu.ca/
===Discussion of {{PAGENAME}} on other websites===
Featured in '''EcoliHub''' Release 1.6.0: http://www.ecolihub.org/ 
Research highlight in '''Nature Methods''' (2009): http://www.nature.com/nmeth/journal/v6/n6/full/nmeth0609-402b.html

eNet

2009-06-29T23:18:04Z

Jdime: Table edited by Jdime via TableEdit

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
[http://www.utoronto.ca/emililab/ Emili Lab] @ University of Toronto, and [http://popolvuh.wlu.ca/ Moreno-Hagelsieb Lab] @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
[http://www.lusara.org/jdime/ Javier Diaz] (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009) <ref name='PMID:19402753'/>
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/] <ref name='PMID:19402753'/>.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
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==Discussion==

==References==
{{RefHelp}}
<references />

==External Links==
eNet: http://ecoli.med.utoronto.ca/ 
Emili lab @ University of Toronto: http://www.utoronto.ca/emililab/ 
Moreno-Hagelsieb lab @ Wilfrid Laurier University: http://popolvuh.wlu.ca/
===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-06-29T23:15:46Z

Jdime: /* External Links */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

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|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
Emili Lab @ University of Toronto, and
Moreno-Hagelsieb Lab @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
Javier Diaz (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009) <ref name='PMID:19402753'/>
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/] <ref name='PMID:19402753'/>.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
{{RefHelp}}
<references />

==External Links==
eNet: http://ecoli.med.utoronto.ca/ 
Emili lab @ University of Toronto: http://www.utoronto.ca/emililab/ 
Moreno-Hagelsieb lab @ Wilfrid Laurier University: http://popolvuh.wlu.ca/
===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-06-29T23:12:15Z

Jdime: Table edited by Jdime via TableEdit

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

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|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
Emili Lab @ University of Toronto, and
Moreno-Hagelsieb Lab @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
Javier Diaz (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009) <ref name='PMID:19402753'/>
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/] <ref name='PMID:19402753'/>.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
{{RefHelp}}
<references />

==External Links==
URL:{{{1|http://ecoli.med.utoronto.ca/}}}

===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-06-29T23:11:27Z

Jdime: /* About eNet */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

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|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
Emili Lab @ University of Toronto, and
Moreno-Hagelsieb Lab @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
Javier Diaz (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009)
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/] <ref name='PMID:19402753'/>.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
{{RefHelp}}
<references />

==External Links==
URL:{{{1|http://ecoli.med.utoronto.ca/}}}

===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-06-29T23:10:54Z

Jdime: /* External Links */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

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|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
Emili Lab @ University of Toronto, and
Moreno-Hagelsieb Lab @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
Javier Diaz (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009)
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/].

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
{{RefHelp}}
<references />

==External Links==
URL:{{{1|http://ecoli.med.utoronto.ca/}}}

===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-06-29T23:10:29Z

Jdime: /* References */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
Emili Lab @ University of Toronto, and
Moreno-Hagelsieb Lab @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
Javier Diaz (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009)
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/].

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
{{RefHelp}}
<references />

==External Links==
[{{{1|link}}} {{PAGENAME}}] URL:{{{1|http://ecoli.med.utoronto.ca/}}}

===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-06-29T23:09:57Z

Jdime: /* References */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
Emili Lab @ University of Toronto, and
Moreno-Hagelsieb Lab @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
Javier Diaz (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009)
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/].

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
{{RefHelp}}
<references />
<ref name='PMID:19402753'/>

==External Links==
[{{{1|link}}} {{PAGENAME}}] URL:{{{1|http://ecoli.med.utoronto.ca/}}}

===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-06-29T23:07:48Z

Jdime: /* About eNet */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
Emili Lab @ University of Toronto, and
Moreno-Hagelsieb Lab @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
Javier Diaz (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009)
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[http://ecoli.med.utoronto.ca/ eNet] is a database of '''gene function prediction in ''Escherichia coli'' K12'''. It exploits the topological properties of physical and functional protein interaction networks integrated via a machine learning algorithm explicitly developed for eNet. eNet provides specific protein functional prediction 'labels' using ontology resources (e.g. [http://www.geneontology.org/ GO], [http://genprotec.mbl.edu/ MultiFun] and [http://www.ncbi.nlm.nih.gov/COG/grace/uni.html COGs] terms) for hypothesis-driven following-up studies. eNet also provides the underlying actual protein interactions and companion groupings of proteins (e.g. multimeric complexes and functional modules) delimited optimizing the [http://www.micans.org/mcl/ Markov clustering algorithm]. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal [http://ecoli.med.utoronto.ca/ http://ecoli.med.utoronto.ca/].

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
{{RefHelp}}
<references />

==External Links==
[{{{1|link}}} {{PAGENAME}}] URL:{{{1|http://ecoli.med.utoronto.ca/}}}

===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-06-29T22:52:08Z

Jdime: /* About eNet */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
Emili Lab @ University of Toronto, and
Moreno-Hagelsieb Lab @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
Javier Diaz (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009)
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[{{{1|http://ecoli.med.utoronto.ca/}}} eNet] is a database of gene function prediction in ''Escherichia coli'' K12. It exploits the topological properties of physical and functional protein interaction networks integrated via machine learning. eNet provides specific protein functional prediction 'labels' (such as GO, MultiFun and COG terms), for hypothesis-driven follow-up studies; as well as the underlying actual interactions and companion groupings of proteins (e.g. multimeric complexes, functional modules and neighbourhoods). All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
{{RefHelp}}
<references />

==External Links==
[{{{1|link}}} {{PAGENAME}}] URL:{{{1|http://ecoli.med.utoronto.ca/}}}

===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-06-29T21:46:34Z

Jdime: Table edited by Jdime via TableEdit

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
Emili Lab @ University of Toronto, and
Moreno-Hagelsieb Lab @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
Javier Diaz (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009)
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096
|-
!align=left {{table heading style}} |Web Services:
||

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[{{{1|http://ecoli.med.utoronto.ca/}}} eNet] is a database of gene function prediction in ''Escherichia coli'' K12. It exploits the topological properties of physical and functional protein interaction networks integrated via machine learning. eNet provides specific protein functional prediction 'labels' (such as GO, MultiFun and COG terms), for hypothesis-driven follow-up studies; as well as the underlying interactions and companion groupings of proteins (node clusters). All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
{{RefHelp}}
<references />

==External Links==
[{{{1|link}}} {{PAGENAME}}] URL:{{{1|http://ecoli.med.utoronto.ca/}}}

===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-06-29T21:42:59Z

Jdime: /* About eNet */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
Emili Lab @ University of Toronto, and
Moreno-Hagelsieb Lab @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
Javier Diaz (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009)
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096
|-
!align=left {{table heading style}} |Web Services:
||
Gene function prediction and annotation of ''E. coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[{{{1|http://ecoli.med.utoronto.ca/}}} eNet] is a database of gene function prediction in ''Escherichia coli'' K12. It exploits the topological properties of physical and functional protein interaction networks integrated via machine learning. eNet provides specific protein functional prediction 'labels' (such as GO, MultiFun and COG terms), for hypothesis-driven follow-up studies; as well as the underlying interactions and companion groupings of proteins (node clusters). All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
{{RefHelp}}
<references />

==External Links==
[{{{1|link}}} {{PAGENAME}}] URL:{{{1|http://ecoli.med.utoronto.ca/}}}

===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-06-29T21:40:10Z

Jdime: /* Content */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
Emili Lab @ University of Toronto, and
Moreno-Hagelsieb Lab @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
Javier Diaz (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009)
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096
|-
!align=left {{table heading style}} |Web Services:
||
Gene function prediction and annotation of ''E. coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[{{{1|http://ecoli.med.utoronto.ca/}}} eNet] is a database of gene function prediction in ''Escherichia coli'' K12. It exploits the topological properties of physical and functional protein interaction networks integrated via machine learning. Our main goal is to provide specific protein functional predictions for hypothesis-driven follow-up studies. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal.

==Content==
Over one-third of the 4,225 protein-coding genes of ''E. coli'' K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all ''E. coli'' proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
{{RefHelp}}
<references />

==External Links==
[{{{1|link}}} {{PAGENAME}}] URL:{{{1|http://ecoli.med.utoronto.ca/}}}

===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-06-29T21:39:33Z

Jdime: /* About eNet */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
Emili Lab @ University of Toronto, and
Moreno-Hagelsieb Lab @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
Javier Diaz (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009)
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096
|-
!align=left {{table heading style}} |Web Services:
||
Gene function prediction and annotation of ''E. coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[{{{1|http://ecoli.med.utoronto.ca/}}} eNet] is a database of gene function prediction in ''Escherichia coli'' K12. It exploits the topological properties of physical and functional protein interaction networks integrated via machine learning. Our main goal is to provide specific protein functional predictions for hypothesis-driven follow-up studies. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal.

==Content==
Over one-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all E. coli proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
{{RefHelp}}
<references />

==External Links==
[{{{1|link}}} {{PAGENAME}}] URL:{{{1|http://ecoli.med.utoronto.ca/}}}

===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-06-29T21:38:43Z

Jdime: Table edited by Jdime via TableEdit

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of ''Escherichia coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
Emili Lab @ University of Toronto, and
Moreno-Hagelsieb Lab @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
Javier Diaz (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009)
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096
|-
!align=left {{table heading style}} |Web Services:
||
Gene function prediction and annotation of ''E. coli'' K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms

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==About eNet==
[{{{1|http://ecoli.med.utoronto.ca/}}} eNet] is a database of gene function prediction in Escherichia coli K12. It exploits the topological properties of physical and functional protein interaction networks integrated via machine learning. Our main goal is to provide specific protein functional predictions for hypothesis-driven follow-up studies. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal.

==Content==
Over one-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all E. coli proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

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[[Category:Databases]]

eNet

2009-06-29T21:35:10Z

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<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of E. coli K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
Emili Lab @ University of Toronto
Moreno-Hagelsieb Lab @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
Javier Diaz (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009)
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096
|-
!align=left {{table heading style}} |Web Services:
||
Gene function prediction and annotation of E. coli K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
|}
</protect>

==About eNet==
[{{{1|http://ecoli.med.utoronto.ca/}}} eNet] is a database of gene function prediction in Escherichia coli K12. It exploits the topological properties of physical and functional protein interaction networks integrated via machine learning. Our main goal is to provide specific protein functional predictions for hypothesis-driven follow-up studies. All eNet datasets and predictions are freely available and can be searched, browsed and downloaded in eNet dedicated web portal.

==Content==
Over one-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all E. coli proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

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==Discussion==

==References==
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==External Links==
[{{{1|link}}} {{PAGENAME}}] URL:{{{1|http://ecoli.med.utoronto.ca/}}}

===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-06-29T21:26:33Z

Jdime: /* Content */

{{Pagetop}} 
{{See|Help:Databases|databases}}

<protect>

{|border="2" cellpadding="4" cellspacing="0" style="margin: 1em 1em 1em 0; border: 1px #aaa solid; border-collapse: collapse;" {{Prettytable}} width='30%' align="right"

|-
!align=left {{table heading style}} |Link/URL:
||
http://ecoli.med.utoronto.ca/
|-
!align=left {{table heading style}} |What:
||
Gene function prediction and annotation of E. coli K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms
|-
!align=left {{table heading style}} |Who:
||
Emili Lab @ University of Toronto
Moreno-Hagelsieb Lab @ Wilfrid Laurier University
|-
!align=left {{table heading style}} |Updates:
||
Javier Diaz (Jdime) - Jun 29, 2009
|-
!align=left {{table heading style}} |Upcoming events:
||
Published paper (Hu et al. 2009)
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096
|-
!align=left {{table heading style}} |Web Services:
||
Gene function prediction and annotation of E. coli K12 proteins using physical protein-protein interactions, genomic context methods and machine learning algorithms

|-class='sortbottom'
|[{{SERVER}}{{SCRIPTPATH}}?title=Special:TableEdit&id=63ce1649aab8b3180235b0af7618f667.164942.J4a492695a68a3&page=164942&pagename={{FULLPAGENAMEE}}&type=1&template=Database_table edit table] ||
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</protect>

==About {{PAGENAME}}==
''Add general information here''
[{{{1|http://ecoli.med.utoronto.ca/}}} {{eNet}}] is a database of Gene function prediction in Escherichia coli K12

==Content==
Over one-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans). Many map to distant clades like Archaea, suggesting involvement in basic prokaryotic traits, while others appear restricted to E. coli, including pathogenic strains. '''To elucidate biological roles of these orphans, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome''' consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated genes, while '''a machine-learning strategy based on network integration implicated the orphans in specific biological processes''', such as protein synthesis, amino acid metabolism, biofilm formation, motility, assembly of the bacterial cell envelope, etc. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

From this website, you can access and download annotations, interactions (proteomic and genomic context-derived) and function predictions for all E. coli proteins analyzed in this study. Also you can explore protein complexes (from proteomic network), functional modules (from genomic context), and functional neighborhoods (from function predictions and preexisting annotations).

For more details you can visit eNet webpage:
http://ecoli.med.utoronto.ca/

or take a look at our publication:
http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1000096

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
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==Discussion==

==References==
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==External Links==
[{{{1|link}}} {{PAGENAME}}] URL:{{{1|http://ecoli.med.utoronto.ca/}}}

===Discussion of {{PAGENAME}} on other websites===

[[Category:Databases]]

eNet

2009-06-29T21:19:30Z

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2009-06-29T21:17:57Z

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eNet

2009-06-29T21:06:15Z

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eNet

2009-06-29T21:05:12Z

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eNet

2009-06-29T21:04:44Z

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eNet

2009-06-29T20:59:01Z

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eNet

2009-06-29T20:55:29Z

Jdime: /* About {{PAGENAME}} */

eNet

2009-06-29T20:39:50Z

Jdime:

eNet

2009-06-29T20:38:08Z

Jdime: New Template:Database Page

{{Pagetop}} 
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<newTableEdit>Template:Database_table</newTableEdit>

==About {{PAGENAME}}==
''Add general information here''
[{{{1|link}}} {{PAGENAME}}] is...

==Content==

==Using {{PAGENAME}} ==
===Browsing===
===Searching===
===Usage examples===
''Add links to additional pages describing success stories here.''

==Other sites with related content {{HelpIcon|Help:Databases}}==

==Technology==
===Web Services/API===

==Discussion==

==References==
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==External Links==
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