Literature DB >> 16772264

Flux balance analysis in the era of metabolomics.

Jong Min Lee1, Erwin P Gianchandani, Jason A Papin.   

Abstract

Flux balance analysis (FBA) has emerged as an effective means to analyse biological networks in a quantitative manner. Much progress has been made on the extension of FBA to incorporate a priori biological knowledge, provide more practical descriptions of observed cell behaviours, and predict the outcome of network perturbations. Metabolomics is independently advancing as a set of high-throughput data acquisition tools providing dynamic profiles of metabolites in an unbiased manner. These data sets are neither yet sufficiently comprehensive nor accurate enough for generating large-scale kinetic models. Thus, there is a pressing need to develop quantitative techniques that can make use of the emerging data and embrace the associated uncertainties. This article reviews recent advances in FBA to meet this need and discusses the utility of FBA as a complement to metabolomics and the expected synergy as a result of combining these two techniques.

Mesh:

Substances:

Year:  2006        PMID: 16772264     DOI: 10.1093/bib/bbl007

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  77 in total

Review 1.  Stable isotope-resolved metabolomics and applications for drug development.

Authors:  Teresa W-M Fan; Pawel K Lorkiewicz; Katherine Sellers; Hunter N B Moseley; Richard M Higashi; Andrew N Lane
Journal:  Pharmacol Ther       Date:  2011-12-23       Impact factor: 12.310

Review 2.  A metabolic network approach for the identification and prioritization of antimicrobial drug targets.

Authors:  Arvind K Chavali; Kevin M D'Auria; Erik L Hewlett; Richard D Pearson; Jason A Papin
Journal:  Trends Microbiol       Date:  2012-01-31       Impact factor: 17.079

Review 3.  Re-membering the body: applications of computational neuroscience to the top-down control of regeneration of limbs and other complex organs.

Authors:  G Pezzulo; M Levin
Journal:  Integr Biol (Camb)       Date:  2015-11-16       Impact factor: 2.192

Review 4.  Mathematical modeling: bridging the gap between concept and realization in synthetic biology.

Authors:  Yuting Zheng; Ganesh Sriram
Journal:  J Biomed Biotechnol       Date:  2010-05-30

5.  Pathway discovery in metabolic networks by subgraph extraction.

Authors:  Karoline Faust; Pierre Dupont; Jérôme Callut; Jacques van Helden
Journal:  Bioinformatics       Date:  2010-03-12       Impact factor: 6.937

6.  Achieving optimal growth through product feedback inhibition in metabolism.

Authors:  Sidhartha Goyal; Jie Yuan; Thomas Chen; Joshua D Rabinowitz; Ned S Wingreen
Journal:  PLoS Comput Biol       Date:  2010-06-03       Impact factor: 4.475

7.  Metabolic modeling and analysis of the metabolic switch in Streptomyces coelicolor.

Authors:  Mohammad T Alam; Maria E Merlo; David A Hodgson; Elizabeth M H Wellington; Eriko Takano; Rainer Breitling
Journal:  BMC Genomics       Date:  2010-03-26       Impact factor: 3.969

8.  Proteomic and network analysis characterize stage-specific metabolism in Trypanosoma cruzi.

Authors:  Seth B Roberts; Jennifer L Robichaux; Arvind K Chavali; Patricio A Manque; Vladimir Lee; Ana M Lara; Jason A Papin; Gregory A Buck
Journal:  BMC Syst Biol       Date:  2009-05-16

Review 9.  Applications of genome-scale metabolic reconstructions.

Authors:  Matthew A Oberhardt; Bernhard Ø Palsson; Jason A Papin
Journal:  Mol Syst Biol       Date:  2009-11-03       Impact factor: 11.429

Review 10.  Predicting drug side-effects by chemical systems biology.

Authors:  Nicholas P Tatonetti; Tianyun Liu; Russ B Altman
Journal:  Genome Biol       Date:  2009-09-02       Impact factor: 13.583

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.