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Bioinformatics
Article . 2009 . Peer-reviewed
Data sources: Crossref
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Bioinformatics
Article
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Bioinformatics
Article . 2010
DBLP
Article . 2009
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An optimization model for metabolic pathways

Authors: Francisco J. Planes; John E. Beasley;

An optimization model for metabolic pathways

Abstract

Abstract Motivation: Different mathematical methods have emerged in the post-genomic era to determine metabolic pathways. These methods can be divided into stoichiometric methods and path finding methods. In this paper we detail a novel optimization model, based upon integer linear programming, to determine metabolic pathways. Our model links reaction stoichiometry with path finding in a single approach. We test the ability of our model to determine 40 annotated Escherichia coli metabolic pathways. We show that our model is able to determine 36 of these 40 pathways in a computationally effective manner. Contact: john.beasley@brunel.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Country
United Kingdom
Related Organizations
Keywords

570, Optimization model, Escherichia coli Proteins, Computational Biology, Escherichia coli metabolic pathways, 004, Integer linear programming, Metabolic pathways, Escherichia coli, Genome, Bacterial, Metabolic Networks and Pathways

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    13
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Average
Top 10%
gold