A novel method for RNA secondary structure prediction

摘要：

In this paper, we propose PSOfold, a particle swarm optimization for RNA secondary structure prediction. PSOfold is based on the recently published IPSO. We present two strategies to improve the performance of IPSO. Firstly, in order to boost the competence in searching an optimal solution, fuzzy logic control is used to adaptively adjust the parameters in PSO. Accordingly, three fuzzy logic controls are designed by which the inertia weight, learning factors and the number of ants are tuned respectively. Secondly, to further settle the stem permutation problem, we put forward a solution conversion strategy (SCS), which can transform discrete values of stems into an ordered stem combination, thereby supplying an enhanced solution to evaluation of objective function. An evaluation of the performance of PSOfold in terms of prediction accuracy is made via comparison with one dynamic programming algorithm mfold and four metaheuristics, IPSO, ACRNA, RnaPredict, SARNA-Predict and mfold for ten individual known structures. PSOfold is able to predict structures with higher prediction accuracy than the other metaheuristic based methods on certain sequences, and has comparable performance compared with mfold.

关键词： Particle swarm optimization RNA secondary structure prediction Fuzxy logic control Solution conversion strategy

作者: Chong Xing Gang Wang Yao Wang Wei Shen Yanchun Liang Zhaohua Ji

作者单位: College of Computer Science and Technology,Jilin University, Changchun, China College of Information Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry,Colle College of Communications Engineering,Jilin University, Changchun, China

会议类型: 国际会议

会议名称: 2011 Seventh International Conference on Natural Computation(第七届自然计算国际会议 ICNC 2011)

会议地点: 上海

会议语种:英文

页码: 1162-1166

在线出版日期: 2011-07-26（万方平台首次上网日期，不代表论文的发表时间）