ΔFBA-Predicting metabolic flux alterations using genome-scale metabolic models and differential transcriptomic data.

ABSTRACT: Genome-scale metabolic models (GEMs) provide a powerful framework for simulating the entire set of biochemical reactions in a cell using a constraint-based modeling strategy called flux balance analysis (FBA). FBA relies on an assumed metabolic objective for generating metabolic fluxes using GEMs. But, the most appropriate metabolic objective is not always obvious for a given condition and is likely context-specific, which often complicate the estimation of metabolic flux alterations between conditions. Here, we propose a new method, called ΔFBA (deltaFBA), that integrates differential gene expression data to evaluate directly metabolic flux differences between two conditions. Notably, ΔFBA does not require specifying the cellular objective. Rather, ΔFBA seeks to maximize the consistency a

SUBMITTER: Ravi S 

PROVIDER: S-EPMC8608322 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature