Literature DB >> 10356245

Toward metabolic phenomics: analysis of genomic data using flux balances.

C H Schilling1, J S Edwards, B O Palsson.   

Abstract

Small genome sequencing and annotations are leading to the definition of metabolic genotypes in an increasing number of organisms. Proteomics is beginning to give insights into the use of the metabolic genotype under given growth conditions. These data sets give the basis for systemically studying the genotype-phenotype relationship. Methods of systems science need to be employed to analyze, interpret, and predict this complex relationship. These endeavors will lead to the development of a new field, tentatively named phenomics. This article illustrates how the metabolic characteristics of annotated small genomes can be analyzed using flux balance analysis (FBA). A general algorithm for the formulation of in silico metabolic genotypes is described. Illustrative analyses of the in silico Escherichia coli K-12 metabolic genotypes are used to show how FBA can be used to study the capabilities of this strain.

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Year:  1999        PMID: 10356245     DOI: 10.1021/bp9900357

Source DB:  PubMed          Journal:  Biotechnol Prog        ISSN: 1520-6033


  38 in total

1.  GeneCensus: genome comparisons in terms of metabolic pathway activity and protein family sharing.

Authors:  J Lin; J Qian; D Greenbaum; P Bertone; R Das; N Echols; A Senes; B Stenger; M Gerstein
Journal:  Nucleic Acids Res       Date:  2002-10-15       Impact factor: 16.971

2.  Genome-scale metabolic model of Helicobacter pylori 26695.

Authors:  Christophe H Schilling; Markus W Covert; Iman Famili; George M Church; Jeremy S Edwards; Bernhard O Palsson
Journal:  J Bacteriol       Date:  2002-08       Impact factor: 3.490

Review 3.  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

4.  The modelling of a primitive 'sustainable' conservative cell.

Authors:  James B Bassingthwaighte
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2001-06       Impact factor: 4.226

Review 5.  Phenomics: the next challenge.

Authors:  David Houle; Diddahally R Govindaraju; Stig Omholt
Journal:  Nat Rev Genet       Date:  2010-12       Impact factor: 53.242

6.  Quantitative flux coupling analysis.

Authors:  Mojtaba Tefagh; Stephen P Boyd
Journal:  J Math Biol       Date:  2018-12-10       Impact factor: 2.259

7.  Analysis of optimality in natural and perturbed metabolic networks.

Authors:  Daniel Segrè; Dennis Vitkup; George M Church
Journal:  Proc Natl Acad Sci U S A       Date:  2002-11-01       Impact factor: 11.205

Review 8.  Whole-Organism Cellular Pathology: A Systems Approach to Phenomics.

Authors:  K C Cheng; S R Katz; A Y Lin; X Xin; Y Ding
Journal:  Adv Genet       Date:  2016-07-29       Impact factor: 1.944

9.  Genome-scale analysis of Streptomyces coelicolor A3(2) metabolism.

Authors:  Irina Borodina; Preben Krabben; Jens Nielsen
Journal:  Genome Res       Date:  2005-06       Impact factor: 9.043

Review 10.  Imaging and modeling of myocardial metabolism.

Authors:  Sebastian Obrzut; Neema Jamshidi; Afshin Karimi; Ulrika Birgersdotter-Green; Carl Hoh
Journal:  J Cardiovasc Transl Res       Date:  2010-02-25       Impact factor: 4.132

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