Systematic evaluation of methods for integration of transcriptomic data into constraint-based models of metabolism.

ABSTRACT: Constraint-based models of metabolism are a widely used framework for predicting flux distributions in genome-scale biochemical networks. The number of published methods for integration of transcriptomic data into constraint-based models has been rapidly increasing. So far the predictive capability of these methods has not been critically evaluated and compared. This work presents a survey of recently published methods that use transcript levels to try to improve metabolic flux predictions either by generating flux distributions or by creating context-specific models. A subset of these methods is then systematically evaluated using published data from three different case studies in E. coli and S. cerevisiae. The flux predictions made by different methods using transcriptomic data are comp

SUBMITTER: Machado D 

PROVIDER: S-EPMC3998872 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature