Guidelines for extracting biologically relevant context-specific metabolic models using gene expression data.

ABSTRACT: Genome-scale metabolic models comprehensively describe an organism's metabolism and can be tailored using omics data to model condition-specific physiology. The quality of context-specific models is impacted by (i) choice of algorithm and parameters and (ii) alternate context-specific models that equally explain the -omics data. Here we quantify the influence of alternate optima on microbial and mammalian model extraction using GIMME, iMAT, MBA, and mCADRE. We find that metabolic tasks defining an organism's phenotype must be explicitly and quantitatively protected. The scope of alternate models is strongly influenced by algorithm choice and the topological properties of the parent genome-scale model with fatty acid metabolism and intracellular metabolite transport contributing much to alt

SUBMITTER: Gopalakrishnan S 

PROVIDER: S-EPMC10258867 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature