Stoichiometric Correlation Analysis: Principles of Metabolic Functionality from Metabolomics Data.

ABSTRACT: Recent advances in metabolomics technologies have resulted in high-quality (time-resolved) metabolic profiles with an increasing coverage of metabolic pathways. These data profiles represent read-outs from often non-linear dynamics of metabolic networks. Yet, metabolic profiles have largely been explored with regression-based approaches that only capture linear relationships, rendering it difficult to determine the extent to which the data reflect the underlying reaction rates and their couplings. Here we propose an approach termed Stoichiometric Correlation Analysis (SCA) based on correlation between positive linear combinations of log-transformed metabolic profiles. The log-transformation is due to the evidence that metabolic networks can be modeled by mass action law and kinetics derive

SUBMITTER: Schwahn K 

PROVIDER: S-EPMC5741659 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature