Accurate flux predictions using tissue-specific gene expression in plant metabolic modeling.

ABSTRACT:

Motivation

The accurate prediction of complex phenotypes such as metabolic fluxes in living systems is a grand challenge for systems biology and central to efficiently identifying biotechnological interventions that can address pressing industrial needs. The application of gene expression data to improve the accuracy of metabolic flux predictions using mechanistic modeling methods such as flux balance analysis (FBA) has not been previously demonstrated in multi-tissue systems, despite their biotechnological importance. We hypothesized that a method for generating metabolic flux predictions informed by relative expression levels between tissues would improve prediction accuracy.

Results

Relative gene expression levels derived from multiple transcriptomic and proteomic dataset

SUBMITTER: Kaste JAM 

PROVIDER: S-EPMC10159652 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature