Detecting DNA-binding Domain From Sequence and Secondary Structure Information Using Kernel-based Technique

摘要：

DNA-binding proteins play an important role invarious intra-and extra-cellular activities.The key in theprotein is DNA-binding region also called DNA-bindingdomain(DBD).However,it is hard to search the DBDsby means of homology search or hidden Markov modelsbecause of a wide variety of the sequences.In this work,we develop a kernel-based machine learning method bycombination of multiple l-vs-l binary classifiers forDNA binding domain prediction.Our result shows that93.73％ accuracy is achieved for multicategory classifierand no less than 90％ accuracy for each binary classifier.By comparison,our classifier performs better than othermachine learning methods.

作者: Wang Fei Chen Lusheng

作者单位: Shanghai key laboratory of Intelligent Information Processing,Fudan University,PRC Department of Computer Science and Engineering,Fudan University,PRC Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education,Jilin Universi

会议类型: 国际会议

会议名称: 2008 3rd International Conference on Intelligent System and Knowledge Engineering(第三届智能系统与知识工程国际会议)(ISKE 2008)

会议地点: 厦门

会议语种:英文

页码: 200-204

在线出版日期: 2008-11-17（万方平台首次上网日期，不代表论文的发表时间）