Prediction of metabolic pathways from genome-scale metabolic networks

The analysis of a variety of data sets (transcriptome arrays, phylogenetic profiles, etc.) yields groups of functionally related genes. In order to determine their biological function, associated gene groups are often projected onto known pathways or tested for enrichment of known functions. However...

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Bibliographic Details
Published in:BioSystems 2011-08, Vol.105 (2), p.109-121
Main Authors: Faust, Karoline, Croes, Didier, van Helden, Jacques
Format: Article
Language:English
Subjects:
Bioinformatics
Computational Biology - methods
Computer Science
Gene Expression Regulation
Genome
Life Sciences
Metabolic network representation
Metabolic Networks and Pathways
Metabolic pathway definition
Metabolic pathway prediction
Metabolomics - methods
Models, Biological
Phylogeny
Subgraph extraction
Transcriptome - methods
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Summary:The analysis of a variety of data sets (transcriptome arrays, phylogenetic profiles, etc.) yields groups of functionally related genes. In order to determine their biological function, associated gene groups are often projected onto known pathways or tested for enrichment of known functions. However, these approaches are not flexible enough to deal with variations or novel pathways. During the last decade, we developed and refined an approach that predicts metabolic pathways from a global metabolic network encompassing all known reactions and their substrates/products, by extracting a subgraph connecting at best a set of seed nodes (compounds, reactions, enzymes or enzyme-coding genes). In this review, we summarize this work, while discussing the problems and pitfalls but also the advantages and applications of network-based metabolic pathway prediction.
ISSN:0303-2647
1872-8324
DOI:10.1016/j.biosystems.2011.05.004