Inference of genetic networks using S-system: information criteria for model selection

In this paper we present an evolutionary approach for inferring the structure and dynamics in gene circuits from observed expression kinetics. For representing the regulatory interactions in a genetic network the decoupled S-system formalism has been used. We proposed an Information Criteria based fitness evaluation for model selection instead of the traditional Mean Squared Error (MSE) based fitness evaluation. A hill climbing local search method has been incorporated in our evolutionary algorithm for attaining the skeletal architecture which is most frequently observed in biological networks. Using small and medium-scale artificial networks we verified the implementation. The reconstruction method identified the correct network topology and predicted the kinetic parameters with high accuracy. Categories and Subject Descriptors J.3 [Life and Medical Sciences]: Biology and genetics; I.2.8 [Problem Solving, Control Methods, and Search]: Heuristic methods General Terms Algorithms, Desig...

• Type: Conference
• Year: 2006
• Where: GECCO
• Authors: Nasimul Noman, Hitoshi Iba
• Keywords: Fitness Evaluation, GECCO 2006, Genetic Network, Observed Expression Kinetics, Optimization