Literature DB >> 24148076

Software platforms to facilitate reconstructing genome-scale metabolic networks.

Joshua J Hamilton1, Jennifer L Reed.   

Abstract

System-level analyses of microbial metabolism are facilitated by genome-scale reconstructions of microbial biochemical networks. A reconstruction provides a structured representation of the biochemical transformations occurring within an organism, as well as the genes necessary to carry out these transformations, as determined by the annotated genome sequence and experimental data. Network reconstructions also serve as platforms for constraint-based computational techniques, which facilitate biological studies in a variety of applications, including evaluation of network properties, metabolic engineering and drug discovery. Bottom-up metabolic network reconstructions have been developed for dozens of organisms, but until recently, the pace of reconstruction has failed to keep up with advances in genome sequencing. To address this problem, a number of software platforms have been developed to automate parts of the reconstruction process, thereby alleviating much of the manual effort previously required. Here, we review four such platforms in the context of established guidelines for network reconstruction. While many steps of the reconstruction process have been successfully automated, some manual evaluation of the results is still required to ensure a high-quality reconstruction. Widespread adoption of these platforms by the scientific community is underway and will be further enabled by exchangeable formats across platforms.
© 2013 Society for Applied Microbiology and John Wiley & Sons Ltd.

Mesh:

Year:  2013        PMID: 24148076     DOI: 10.1111/1462-2920.12312

Source DB:  PubMed          Journal:  Environ Microbiol        ISSN: 1462-2912            Impact factor:   5.491


  23 in total

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Review 5.  Metabolic network modeling of microbial communities.

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Review 9.  A constraint-based modelling approach to metabolic dysfunction in Parkinson's disease.

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Journal:  Comput Struct Biotechnol J       Date:  2015-09-02       Impact factor: 7.271

10.  A genome-scale metabolic flux model of Escherichia coli K-12 derived from the EcoCyc database.

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