Literature DB >> 15494745

Genome-scale models of microbial cells: evaluating the consequences of constraints.

Nathan D Price1, Jennifer L Reed, Bernhard Ø Palsson.   

Abstract

Microbial cells operate under governing constraints that limit their range of possible functions. With the availability of annotated genome sequences, it has become possible to reconstruct genome-scale biochemical reaction networks for microorganisms. The imposition of governing constraints on a reconstructed biochemical network leads to the definition of achievable cellular functions. In recent years, a substantial and growing toolbox of computational analysis methods has been developed to study the characteristics and capabilities of microorganisms using a constraint-based reconstruction and analysis (COBRA) approach. This approach provides a biochemically and genetically consistent framework for the generation of hypotheses and the testing of functions of microbial cells.

Mesh:

Year:  2004        PMID: 15494745     DOI: 10.1038/nrmicro1023

Source DB:  PubMed          Journal:  Nat Rev Microbiol        ISSN: 1740-1526            Impact factor:   60.633


  357 in total

Review 1.  Computational tools for the synthetic design of biochemical pathways.

Authors:  Marnix H Medema; Renske van Raaphorst; Eriko Takano; Rainer Breitling
Journal:  Nat Rev Microbiol       Date:  2012-01-23       Impact factor: 60.633

2.  Superessential reactions in metabolic networks.

Authors:  Aditya Barve; João Frederico Matias Rodrigues; Andreas Wagner
Journal:  Proc Natl Acad Sci U S A       Date:  2012-04-16       Impact factor: 11.205

Review 3.  Network biology methods integrating biological data for translational science.

Authors:  Gurkan Bebek; Mehmet Koyutürk; Nathan D Price; Mark R Chance
Journal:  Brief Bioinform       Date:  2012-03-05       Impact factor: 11.622

Review 4.  A road map for the development of community systems (CoSy) biology.

Authors:  Karsten Zengler; Bernhard O Palsson
Journal:  Nat Rev Microbiol       Date:  2012-03-27       Impact factor: 60.633

5.  Prediction of metabolic fluxes by incorporating genomic context and flux-converging pattern analyses.

Authors:  Jong Myoung Park; Tae Yong Kim; Sang Yup Lee
Journal:  Proc Natl Acad Sci U S A       Date:  2010-08-02       Impact factor: 11.205

6.  In silico identification of gene amplification targets for improvement of lycopene production.

Authors:  Hyung Seok Choi; Sang Yup Lee; Tae Yong Kim; Han Min Woo
Journal:  Appl Environ Microbiol       Date:  2010-03-26       Impact factor: 4.792

7.  The challenges of integrating multi-omic data sets.

Authors:  Bernhard Palsson; Karsten Zengler
Journal:  Nat Chem Biol       Date:  2010-11       Impact factor: 15.040

8.  Deep epistasis in human metabolism.

Authors:  Marcin Imielinski; Calin Belta
Journal:  Chaos       Date:  2010-06       Impact factor: 3.642

9.  Shifts in metabolic scaling, production, and efficiency across major evolutionary transitions of life.

Authors:  John P DeLong; Jordan G Okie; Melanie E Moses; Richard M Sibly; James H Brown
Journal:  Proc Natl Acad Sci U S A       Date:  2010-06-29       Impact factor: 11.205

Review 10.  How to make a minimal genome for synthetic minimal cell.

Authors:  Liu-Yan Zhang; Su-Hua Chang; Jing Wang
Journal:  Protein Cell       Date:  2010-06-04       Impact factor: 14.870

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