RNA Secondary Structure Prediction in Soft Computing Framework: A Review

摘要：

This article provides an overview of the application of certain soft computing tools namely, genetic algorithms (GAs), simulated annealing (SA), and artificial neural networks (ANNs) in certain tasks of RNA secondary structure prediction. Different tasks like prediction of helix, bulge, hairpin curve, internal loop, and multiloop are, first of all, described along with their basic features. The relevance of using soft computing tools to these problems is then mentioned. These are followed by different approaches along with their merits for addressing some of the aforesaid tasks. Finally some limitations of the current research activity are provided.

关键词： RNA combinatorial optimization dynamic programming soft computing genetic algorithms simulated annealing neural networks.

作者: Shubhra Sankar Ray Munia Bachhar Sankar K.Pal Fellow IEEE

作者单位: Center for Soft Computing Research,Kolkata 700108,India Machine Intelligence Unit Indian Statistical Center for Soft Computing Research,Kolkata 700108,India

会议类型: 国际会议

会议名称: 2010 3rd IEEE International Conference on Computer Science and Information Technology(第三届IEEE计算机科学与信息技术国际会议 ICCSIT 2010)

会议地点: 成都

会议语种:英文

页码: 430-435

在线出版日期: 2010-07-07（万方平台首次上网日期，不代表论文的发表时间）