PMID:18828895
| Citation |
Saito, S, Aburatani, S and Horimoto, K (2008) Network evaluation from the consistency of the graph structure with the measured data. BMC Syst Biol 2:84 |
|---|---|
| Abstract |
A knowledge-based network, which is constructed by extracting as many relationships identified by experimental studies as possible and then superimposing them, is one of the promising approaches to investigate the associations between biological molecules. However, the molecular relationships change dynamically, depending on the conditions in a living cell, which suggests implicitly that all of the relationships in the knowledge-based network do not always exist. Here, we propose a novel method to estimate the consistency of a given network with the measured data: i) the network is quantified into a log-likelihood from the measured data, based on the Gaussian network, and ii) the probability of the likelihood corresponding to the measured data, named the graph consistency probability (GCP), is estimated based on the generalized extreme value distribution. |
| Links |
PubMed PMC2566979 Online version:10.1186/1752-0509-2-84 |
| Keywords |
Adaptation, Biological/genetics; Cell Physiological Phenomena; Computer Simulation; Confidence Intervals; Databases, Genetic; Escherichia coli/genetics; Escherichia coli/metabolism; Gene Expression Profiling/methods; Gene Regulatory Networks/physiology; Knowledge Bases; Likelihood Functions; Models, Biological; Neural Networks (Computer); Normal Distribution; Oligonucleotide Array Sequence Analysis; Predictive Value of Tests; Protein Interaction Mapping/methods; Reproducibility of Results; Research Design; SOS Response (Genetics)/genetics; Sample Size; Systems Biology/methods |
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