PMID:21823757
| Citation |
Bordron, P, Eveillard, D and Rusu, I (2011) Integrated analysis of the gene neighbouring impact on bacterial metabolic networks. IET Syst Biol 5:261-8 |
|---|---|
| Abstract |
Different levels of abstraction are needed to represent a living system. Unfortunately information of different nature is not superposable in an obvious way, but requires a dedicated framework. Because biological abstractions, i.e., genomic or metabolic information, can be easily represented as graphs, it is intuitive to integrate them into a unique graph, in which one can perform graph analysis for investigating a given biological assumption. This study follows such a philosophy and completes a genome and metabolome combination. In a such integrated framework and as illustration, we applied a graph analysis that automatically investigates impacts of the gene adjacency to predict functional relationships between genes and reactions. Our approach, called SIPPER, creates a weighted graph, in which the weights rely on the given relationship between genes, and computes (alternative) chains of reactions catalysed by genes. This method, as a generalisation of methods already published, can be easily adapted to several biological assumptions, properties or measures. This paper evaluates SIPPER on Escherichia coli. We automatically extract subgraphs, called k-SIPs, and quantify their interest in both genomic and metabolic contexts by showing functional compounds like operons or functional modules. |
| Links |
PubMed Online version:10.1049/iet-syb.2010.0070 |
| Keywords |
Computer Simulation; Escherichia coli/physiology; Escherichia coli Proteins/physiology; Gene Expression Regulation, Bacterial/physiology; Models, Biological; Signal Transduction/physiology |
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