Analyzing Metabolomics Data for Automated Prediction of Underlying Biological Mechanisms
Metabolites are intermediates and products of metabolism. With the recent advances in experimental technologies, such as gas chromatography and mass spectrometry, the number of metabolites that can be measured in biofluids has rapidly increased. The large number and breath of the metabolites represents a challenge to an informed interpretation of the results, when the goal is to determine the biochemical mechanisms that are responsible for the observed changes. There is thus a need for computational tools to help biologists and clinical researchers to derive meaningful interpretations of metabolomics data. This talk describes a technique for automated interpretation and analysis of metabolomics data via existing metabolic networks. We also briefly describe our current prototype system that implements our technique.