Literature DB >> 12209793

A functional genomics approach using metabolomics and in silico pathway analysis.

Jochen Förster1, Andreas Karoly Gombert, Jens Nielsen.   

Abstract

In the field of functional genomics increasing effort is being undertaken to analyze the function of orphan genes using metabolome data. Improved analytical equipment allows screening simultaneously for a high number of metabolites. Such metabolite profiles are analyzed using multivariate data analysis techniques and changes in the genotype will in many cases lead to different metabolite profiles. Here, a theoretical framework that may be applied to identify the function of orphan genes is presented. The approach is based on a combination of metabolome analysis combined with in silico pathway analysis. Pathway analysis may be carried out using convex analysis and a change in the active pathway structure of deletion mutants expressed in a different metabolite profile may disclose the function or the functional class of an orphan gene. The concept is illustrated using a simplified model for growth of Saccharomyces cerevisiae. Copyright 2002 Wiley Periodicals, Inc.

Entities:  

Mesh:

Year:  2002        PMID: 12209793     DOI: 10.1002/bit.10378

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  17 in total

Review 1.  Microbial metabolomics: replacing trial-and-error by the unbiased selection and ranking of targets.

Authors:  Mariët J van der Werf; Renger H Jellema; Thomas Hankemeier
Journal:  J Ind Microbiol Biotechnol       Date:  2005-05-14       Impact factor: 3.346

2.  CBFA: phenotype prediction integrating metabolic models with constraints derived from experimental data.

Authors:  Rafael Carreira; Pedro Evangelista; Paulo Maia; Paulo Vilaça; Marcellinus Pont; Jean-François Tomb; Isabel Rocha; Miguel Rocha
Journal:  BMC Syst Biol       Date:  2014-12-03

Review 3.  Which metabolic pathways generate and characterize the flux space? A comparison among elementary modes, extreme pathways and minimal generators.

Authors:  Francisco Llaneras; Jesús Picó
Journal:  J Biomed Biotechnol       Date:  2010-05-11

4.  Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network.

Authors:  Jochen Förster; Iman Famili; Patrick Fu; Bernhard Ø Palsson; Jens Nielsen
Journal:  Genome Res       Date:  2003-02       Impact factor: 9.043

5.  Expression of phosphofructokinase in Neisseria meningitidis.

Authors:  Gino J E Baart; Marc Langenhof; Bas van de Waterbeemd; Hendrik-Jan Hamstra; Bert Zomer; Leo A van der Pol; E C Beuvery; Johannes Tramper; Dirk E Martens
Journal:  Microbiology (Reading)       Date:  2009-10-01       Impact factor: 2.777

6.  Imbalance of heterologous protein folding and disulfide bond formation rates yields runaway oxidative stress.

Authors:  Keith E J Tyo; Zihe Liu; Dina Petranovic; Jens Nielsen
Journal:  BMC Biol       Date:  2012-03-01       Impact factor: 7.431

7.  Cell functional enviromics: unravelling the function of environmental factors.

Authors:  Ana P Teixeira; João Ml Dias; Nuno Carinhas; Marcos Sousa; João J Clemente; António E Cunha; Moritz von Stosch; Paula M Alves; Manuel Jt Carrondo; Rui Oliveira
Journal:  BMC Syst Biol       Date:  2011-06-06

8.  Evolutionary programming as a platform for in silico metabolic engineering.

Authors:  Kiran Raosaheb Patil; Isabel Rocha; Jochen Förster; Jens Nielsen
Journal:  BMC Bioinformatics       Date:  2005-12-23       Impact factor: 3.169

9.  A metabolic model of Lipomyces starkeyi for predicting lipogenesis potential from diverse low-cost substrates.

Authors:  Wei Zhou; Yanan Wang; Junlu Zhang; Man Zhao; Mou Tang; Wenting Zhou; Zhiwei Gong
Journal:  Biotechnol Biofuels       Date:  2021-07-01       Impact factor: 6.040

10.  Use of physiological constraints to identify quantitative design principles for gene expression in yeast adaptation to heat shock.

Authors:  Ester Vilaprinyo; Rui Alves; Albert Sorribas
Journal:  BMC Bioinformatics       Date:  2006-04-03       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.