Title of the Talk: Human Metabolic Network Analysis
Abstract: Metabolic network modeling of biological systems involves the analysis and prediction of metabolic flux distributions under diverse physiological and genetic conditions. Constraint-based modeling is a computational approach for analyzing the function of large-scale metabolic networks through relying solely on simple physical- chemical constraints. Despite the progress in applying constraint-based modeling to study the metabolism of microorganisms, large-scale modeling of human metabolism is still in its infancy. We present several novel constraint-based methods for studying human metabolism via existing comprehensive reconstructions of the global human metabolic network: (i) A method for automatically reconstructing tissue-specific metabolic network models and its application to reconstruct a genome-scale model of liver metabolism. (ii) Predicting selective drug targets in cancer through metabolic networks. Our results lay down the computational basis for the genome-wide study of normal and abnormal human metabolism in a tissue-specific manner.