Towards dynamic genome-scale models.

ABSTRACT: The analysis of the dynamic behaviour of genome-scale models of metabolism (GEMs) currently presents considerable challenges because of the difficulties of simulating such large and complex networks. Bacterial GEMs can comprise about 5000 reactions and metabolites, and encode a huge variety of growth conditions; such models cannot be used without sophisticated tool support. This article is intended to aid modellers, both specialist and non-specialist in computerized methods, to identify and apply a suitable combination of tools for the dynamic behaviour analysis of large-scale metabolic designs. We describe a methodology and related workflow based on publicly available tools to profile and analyse whole-genome-scale biochemical models. We use an efficient approximative stochastic simulatio

SUBMITTER: Gilbert D 

PROVIDER: S-EPMC6781584 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature