Identification of Dominant Paths for Biochemical Reaction Networks from Incomplete Data

Stanford University, Stanford CA

Investigators

Abstract

John Ross of Stanford University is supported by an award from the Theoretical and Computational Chemistry program within the Division of Chemistry for the development of methods and tools to determine dominant reaction pathways in complex biochemical networks. The approach is based on the use of a generalized Fisher law, combined with a renormalization group approach, and applied to response experiments. Statistical approaches for identifying dominant reaction pathways from incomplete data collected from response experiments have been introduced. These methods permit the analysis of incomplete experimental data in biochemical reactions. The broader impacts of this work involve an international collaboration to apply these methods to study several biological systems: to the study of yeast metabolism and blood coagulation. It is expected that the blood coagulation model will be implemented in clinical software programs for improved prediction of the dosage of oral coagulants.