Using resource constraints derived from genomic and proteomic data in metabolic network models

Abstract

The increasing amount of available high-content data in genomics, proteomics, and metabolomics has significantly improved the predictive power and model accuracy of genome-scale metabolic network models in recent years. We review recent constraint-based modeling approaches that incorporate genomics and proteomics data to form resource allocation models. Different modeling approaches to build resource allocation models and the related enzyme-constrained genome-scale metabolic models are discussed and evaluated with respect to differences regarding model features. In addition, an overview of the data required to construct, simulate and validate models for the different approaches is given, together with a list of relevant databases.