DomSVR: Domain Boundary Prediction with Support Vector Regression and Evolutionary Information

摘要：

Protein domains are autonomous folding units and are fundamental structural and functional units of proteins. Protein domain boundaries are helpful to the classification of proteins and understanding the evolutions, structures and functions of proteins. In this paper, we propose a support vector regression based method to locate residues at protein domain boundaries with a combination of evolutionary information including sequence profiles, predicted secondary structures, predicted relative solvent accessibility, and profiles from HSSP items. Our proposed model achieved an average sensitivity of～37％ and an average specificity of～77％ on domain boundary identification on our dataset of multi-domain proteins and showed better predictive performance than previous domain identification models.

关键词： domain boundary support vector regression sequence profile secondary structure

作者: Peng Chen Chunmei Liu Legand Burge Mohammad Mahmood William Southerland Clay Gloster

作者单位: Department of Systems and Computer Science,Howard University 2300 Sixth Street,NW Washington,DC 2005 Department of Mathematics Howard University Washington,DC 20059,USA Department of Biochemistry Howard University Washington,DC 20059,USA Department of Electrical and Computer Engineering Howard University Washington,DC 20059,USA

会议类型: 国际会议

会议名称: The 3rd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2009)(第三届生物信息与生物医学工程国际会议)

会议地点: 北京

会议语种:英文

页码: 1-5

在线出版日期: 2009-06-11（万方平台首次上网日期，不代表论文的发表时间）