Splice sites identification based on multiclass feature representation

摘要：

Accurate splice site identification is a critical component of eukaryotic gene prediction and efficient feature representation plays a key role in the splice sites identification. We propose a splice sites identification algorithm based on multiclass feature representation (denoted as MFR), which uses various features effective for splice sites identification, including position-dependent features, regiondependent motif features, composite-nucleotides features and region-dependent statistical features. The experimental results on HS3D and ?? NN269 acceptor data sets show that our algorithm outperforms current state-of-art algorithms. Besides, our algorithm has lower space complexity and higher time efficiency.

关键词： splice sites identification feature representation

作者: Xuejiao Kang Qinke Peng Xin Cheng Quanwei Zhang

作者单位: State Key Laboratory for Manufacturing Systems Engineering MOE Key Laboratory for Intelligent Networks and Network Security Systems Engineering Institute Xian Jiaotong University XiAn, China

会议类型: 国际会议

会议名称: The 13th IEEE Joint International Computer Science and Information Technology Conference(2011年第13届IEEE联合国际计算机科学与信息技术会议 JICSIT 2011)

会议地点: 重庆

会议语种:英文

页码: 1828-1832

在线出版日期: 2011-08-20（万方平台首次上网日期，不代表论文的发表时间）