蛋白质功能预测的蚁群优化算法

Abstract

Abstract: Protein function prediction is one of the most challenging problems in the post-genome era.For high-throughput data,it can save time and cost considerably by using prediction algorithms with high performance.Using a global optimization model based on protein-protein interaction networks,anant colony optimization algorithm for protein function prediction is proposed.The proposed algorithm can use the benefits of global optimization model and the priori knowledge in the network simultaneously and improves its search efficiency.The simulation results show that the ant colony optimization has good performance on protein function prediction,and good fault-tolerant for false positive and false negative data in the protein-protein interaction network.

Key words: protein-protein interaction network, function prediction, ant colony optimization, global optimization model

CLC Number:

Q811

WU Chao, ZHONG Yi-wen. Protein Function Prediction Using Ant Colony Optimization Algorithm[J].Journal of Guangxi Normal University(Natural Science Edition), 2011, 29(3): 136-141.

References

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