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《Computer Science》 2012-09
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CGP-WPSO Hybrid Algorithm for Gene Regulatory Network Modeling

CAI Xin-ye NIU Yun HUANG Zhi-qiu FAN Da-juan(College of Information Science and Technology,Nanjing University of Aeronautics & Astronautics,Nanjing 210016,China)  
The phenotype of the crops can be predicted through the gene regulatory network(GRN),which is important for the global food security.This paper proposed a Cartesian genetic programming and linear decreasing inertia weight particle swarm optimization algorithm for GRN modeling.To verify the effectiveness of the proposed algorithm,we applied it to the recovery of the Arabidopsis flowering time control system.The computer simulation indicates that our proposed algorithm is able to infer the GRN model which can predict the phenotype of the crops fairly accurately based on its genotype and environmental conditions.
【Fund】: 国家高技术研究发展计划(863计划)(2009AA010307)资助
【CateGory Index】: TP18
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