Literature DB >> 20863283

Building and analysing genome-scale metabolic models.

David A Fell1, Mark G Poolman, Albert Gevorgyan.   

Abstract

Reconstructing a model of the metabolic network of an organism from its annotated genome sequence would seem, at first sight, to be one of the most straightforward tasks in functional genomics, even if the various data sources required were never designed with this application in mind. The number of genome-scale metabolic models is, however, lagging far behind the number of sequenced genomes and is likely to continue to do so unless the model-building process can be accelerated. Two aspects that could usefully be improved are the ability to find the sources of error in a nascent model rapidly, and the generation of tenable hypotheses concerning solutions that would improve a model. We will illustrate these issues with approaches we have developed in the course of building metabolic models of Streptococcus agalactiae and Arabidopsis thaliana.

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Year:  2010        PMID: 20863283     DOI: 10.1042/BST0381197

Source DB:  PubMed          Journal:  Biochem Soc Trans        ISSN: 0300-5127            Impact factor:   5.407


  13 in total

1.  Model-based biotechnological potential analysis of Kluyveromyces marxianus central metabolism.

Authors:  A Pentjuss; E Stalidzans; J Liepins; A Kokina; J Martynova; P Zikmanis; I Mozga; R Scherbaka; H Hartman; M G Poolman; D A Fell; A Vigants
Journal:  J Ind Microbiol Biotechnol       Date:  2017-04-25       Impact factor: 3.346

2.  Responses to light intensity in a genome-scale model of rice metabolism.

Authors:  Mark G Poolman; Sudip Kundu; Rahul Shaw; David A Fell
Journal:  Plant Physiol       Date:  2013-05-02       Impact factor: 8.340

3.  Functional genomics tools applied to plant metabolism: a survey on plant respiration, its connections and the annotation of complex gene functions.

Authors:  Wagner L Araújo; Adriano Nunes-Nesi; Thomas C R Williams
Journal:  Front Plant Sci       Date:  2012-09-06       Impact factor: 5.753

4.  FFCA: a feasibility-based method for flux coupling analysis of metabolic networks.

Authors:  Laszlo David; Sayed-Amir Marashi; Abdelhalim Larhlimi; Bettina Mieth; Alexander Bockmayr
Journal:  BMC Bioinformatics       Date:  2011-06-15       Impact factor: 3.169

5.  Flux-balance modeling of plant metabolism.

Authors:  Lee J Sweetlove; R George Ratcliffe
Journal:  Front Plant Sci       Date:  2011-08-11       Impact factor: 5.753

Review 6.  Integrated network analysis and effective tools in plant systems biology.

Authors:  Atsushi Fukushima; Shigehiko Kanaya; Kozo Nishida
Journal:  Front Plant Sci       Date:  2014-11-04       Impact factor: 5.753

Review 7.  A Diverse Community To Study Communities: Integration of Experiments and Mathematical Models To Study Microbial Consortia.

Authors:  Antonella Succurro; Fiona Wanjiku Moejes; Oliver Ebenhöh
Journal:  J Bacteriol       Date:  2017-07-11       Impact factor: 3.490

8.  The intertwined metabolism during symbiotic nitrogen fixation elucidated by metabolic modelling.

Authors:  Thomas Pfau; Nils Christian; Shyam K Masakapalli; Lee J Sweetlove; Mark G Poolman; Oliver Ebenhöh
Journal:  Sci Rep       Date:  2018-08-21       Impact factor: 4.379

9.  Gsmodutils: a python based framework for test-driven genome scale metabolic model development.

Authors:  James Gilbert; Nicole Pearcy; Rupert Norman; Thomas Millat; Klaus Winzer; John King; Charlie Hodgman; Nigel Minton; Jamie Twycross
Journal:  Bioinformatics       Date:  2019-09-15       Impact factor: 6.937

Review 10.  Review and perspective on mathematical modeling of microbial ecosystems.

Authors:  Antonella Succurro; Oliver Ebenhöh
Journal:  Biochem Soc Trans       Date:  2018-03-14       Impact factor: 5.407

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