研究者情報 | 神奈川大学

チョウ　ゼンシュン Zhang Shanjun 張　善俊所属神奈川大学情報学部計算機科学科神奈川大学大学院理学研究科理学専攻（情報科学領域）職種教授
言語種別	日本語
発行・発表の年月	2009/11
形態種別	その他
査読	査読あり
標題	Protein Structure Prediction with EPSO in Toy Model
執筆形態	共著
掲載誌名	IEEE Computer Society Conference Publications
巻・号・頁	2009 Second International Conference on Intelligent Networks and Intelligent Systems,,673-676頁
著者・共著者	Hongbing Zhu, Chengdong Pu, Xiaoli Lin, Jinguang Gu, Shanjun Zhang, and Mengsi Su
概要	Predicting the structure of protein through its sequence of amino acids is a complex and challenging problem in computational biology. Though toy model is one of the simplest and effective models, it is still extremely difficult to predict its structure as the increase of amino acids. Particle swarm optimization (PSO) is a swarm intelligence algorithm, has been successfully applied to many optimization problems and shown its high search speed in these applications. However, as the dimension and the number of local optima of problems increase, PSO is easily trapped in local optima. We have proposed an improved PSO algorithm is called EPSO in the other paper, which has greatly improved the ability of escaping form local optima. In this paper we applied EPSO to the structure prediction of toy model both on artificial and real protein sequences and compared with the results reported in other literatures. The experimental results demonstrated that EPSO was efficient in protein structure prediction problem in toy model.