Functional integration of a metabolic network model and expression data without arbitrary thresholding.

ABSTRACT:

Motivation

Flux balance analysis (FBA) has been used extensively to analyze genome-scale, constraint-based models of metabolism in a variety of organisms. The predictive accuracy of such models has recently been improved through the integration of high-throughput expression profiles of metabolic genes and proteins. However, extensions of FBA often require that such data be discretized a priori into sets of genes or proteins that are either 'on' or 'off'. This procedure requires selecting relatively subjective expression thresholds, often requiring several iterations and refinements to capture the expression dynamics and retain model functionality.

Results

We present a method for mapping expression data from a set of environmental, genetic or temporal conditions onto a metabo

SUBMITTER: Jensen PA 

PROVIDER: S-EPMC6276961 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature