A Model Reduction Technique for Stochastic Biochemical Kinetics

Abstract-- Modeling the intermolecular reactions in a single cell is a critical problem in computational biology. Biochemical reaction systems often involve species in both low and large population numbers, as is the case of genetic regulatory networks. Then, random fluctuations due to small population numbers may be significant. Hence, stochastic mathematical models are needed to accurately capture the dynamics of the system. In addition, biochemical systems are typically quite complex, involving a large number of components and interactions. This complexity posses great challenges for simulation and analysis of the system. Model reduction techniques aim at reducing the complexity of the system by selecting only the important reactions and species, while retaining the essential features of the full system. We analyze in this paper a novel model reduction technique for stochastic models of biochemical reactions based on sensitivity analysis. We apply this approach to a model of transcr...

• Type: Journal
• Year: 2010
• Where: BIOCOMP
• Authors: Silvana Ilie, Ekaterina Kudashkina
• Keywords: Biochemical Reactions, BIOCOMP 2010, Bioinformatics, Model Reduction Technique, Population Numbers