Literature DB >> 21863502

Genome-scale metabolic models of Saccharomyces cerevisiae.

Intawat Nookaew1, Roberto Olivares-Hernández, Sakarindr Bhumiratana, Jens Nielsen.   

Abstract

Systematic analysis of Saccharomyces cerevisiae metabolic functions and pathways has been the subject of extensive studies and established in many aspects. With the reconstruction of the yeast genome-scale metabolic (GSM) network and in silico simulation of the GSM model, the nature of the underlying cellular processes can be tested and validated with the increasing metabolic knowledge. GSM models are also being exploited in fundamental research studies and industrial applications. In this chapter, the principle concepts for construction, simulation and validation of GSM models, progressive applications of the yeast GSM models, and future perspectives are described. This will support and encourage researchers who are interested in systemic analysis of yeast metabolism and systems biology.

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Year:  2011        PMID: 21863502     DOI: 10.1007/978-1-61779-173-4_25

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  4 in total

1.  Genome-Scale Metabolic Modeling from Yeast to Human Cell Models of Complex Diseases: Latest Advances and Challenges.

Authors:  Yu Chen; Gang Li; Jens Nielsen
Journal:  Methods Mol Biol       Date:  2019

2.  Improving the flux distributions simulated with genome-scale metabolic models of Saccharomyces cerevisiae.

Authors:  Rui Pereira; Jens Nielsen; Isabel Rocha
Journal:  Metab Eng Commun       Date:  2016-05-13

3.  Flux prediction using artificial neural network (ANN) for the upper part of glycolysis.

Authors:  Anamya Ajjolli Nagaraja; Nicolas Fontaine; Mathieu Delsaut; Philippe Charton; Cedric Damour; Bernard Offmann; Brigitte Grondin-Perez; Frederic Cadet
Journal:  PLoS One       Date:  2019-05-08       Impact factor: 3.240

4.  From metagenomic data to personalized in silico microbiotas: predicting dietary supplements for Crohn's disease.

Authors:  Eugen Bauer; Ines Thiele
Journal:  NPJ Syst Biol Appl       Date:  2018-08-01
  4 in total

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