Predicting Protein Phosphorylation Sites with Neural-genetic Network Algorithm

摘要：

Protein phosphorylation affects a multitude of cellular signaling processes. By predicting protein phosphorylation sites from primary protein sequences, we can obtain much valuable information that can form the basis for further research. Here,we present a neural-genetic network algorithm that predicts phosphorylation sites in proteins. Aided by a genetic algorithm to optimize the weight values within the ueural network,the new algorithm has demonstrated a high accuracy of 75.1％, 82.7％and 79.2％ in predicting the phosphorylated S, T and Y sites,respectively. The prediction system can be applied to other prediction tasks in the field of protein bioinformatics.

关键词： protein phosphorylation sites prediction neural network genetic algorithm

作者: Yu-Rong Tang Yong-Zi Chen Zhi-Ya Sheng Ziding Zhang

作者单位: College of Biological Sciences China Agricultural University, CAU Beijing, China

会议类型: 国际会议

会议名称: The 1st International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2007)(首届IEEE生物信息与生物医学工程国际会议)

会议地点: 武汉

会议语种:英文

页码: 113-116

在线出版日期: 2007-07-06（万方平台首次上网日期，不代表论文的发表时间）