Predicting PPII by Artificial Neural Network with a Modified Sequence Coding Method

摘要：

Polypro line type Ⅱ (PPII) secondary structures are somewhat rare on proteins. Few works have been made to predict PPII with machine learning approaches. This paper predicted PPII secondary structure with BP-model neural network based on preprocessing protein sequences, and compared two numerical sequence coding methods in PPII,the traditional binary vector sequence coding method and the modified binary vector sequence coding method allowing for neighboring amino-acid residues effect.Results show that the modified sequence coding method is better than the traditional sequence coding method in predicting PPII; the sensitivity can reach 82.5％.

关键词： Artificial Neural Network BP-model Protein Secondary Structure and Prediction of Polypro line Type Ⅱ

作者: Kezhong Lu Lanjuan Sun Wenbo Xu

作者单位: Department of Computer Science, Chizhou Teachers College, Chizhou 247000,China School of Information Technology, Southern Yangtze University, Wuxi 214036, China

会议类型: 国际会议

会议名称: 2006 International Symposium on Distributed Computing and Applications to Business,Engineering and Science(2006年国际电子、工程及科学领域的分布式计算应用学术研讨会)

会议地点: 杭州

会议语种:英文

页码: 763-766

在线出版日期: 2006-10-12（万方平台首次上网日期，不代表论文的发表时间）