Use of genome-scale metabolic models in evolutionary systems biology

Balázs Papp*, Balázs Szappanos, Richard A. Notebaart

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

9 Citations (Scopus)


One of the major aims of the nascent field of evolutionary systems biology is to test evolutionary hypotheses that are not only realistic from a population genetic point of view but also detailed in terms of molecular biology mechanisms. By providing a mapping between genotype and phenotype for hundreds of genes, genome-scale systems biology models of metabolic networks have already provided valuable insights into the evolution of metabolic gene contents and phenotypes of yeast and other microbial species. Here we review the recent use of these computational models to predict the fitness effect of mutations, genetic interactions, evolutionary outcomes, and to decipher the mechanisms of mutational robustness. While these studies have demonstrated that even simplified models of biochemical reaction networks can be highly informative for evolutionary analyses, they have also revealed the weakness of this modeling framework to quantitatively predict mutational effects, a challenge that needs to be addressed for future progress in evolutionary systems biology.

Original languageEnglish
Title of host publicationYeast Systems Biology
Subtitle of host publicationMethods and Protocols
EditorsJuan I. Castrillo, Stephen G. Oliver
PublisherHumana Press
ISBN (Electronic)9781617791734
ISBN (Print)9781617791727
Publication statusPublished - 2011
Externally publishedYes

Publication series

NameMethods in Molecular Biology
ISSN (Print)1064-3745


  • constraint-based modeling
  • fitness landscape
  • Flux balance analysis (FBA)
  • gene essentiality
  • genetic interaction
  • genome evolution
  • metabolic network
  • Saccharomyces cerevisiae


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