计算机应用与软件2011，Vol.28Issue(6)：1-4,42,5.
基于多数据域描述的转录因子结合位点识别
TRANSCRIPTION FACTOR BINDING SITES RECOGNITION BASED ON MULTIPLE DATA DOMAIN DESCRIPTION
摘要
Abstract
Transcription factor binding site recognition plays an important role in the comprehension of transcription regulation mechanism,and is the great challenge the post-genome era encounters as well. In this paper we present a multi-task learning based approach for the problem of transcription factor binding sites (TFBS) recognition. Firstly, a new multiple data domain description model was established, it was based on the theory of multi-task learning; then in combination with kernel methods, a multiple classification recognition algorithm for transcription factor binding site was designed. Finally,the real data set retrieved from TRANSFAC database was tested with cross-validation.Experimental result indicated that this approach can fully use scarce training samples and effectually capture the inter-class relations ,therefore attained quite high accuracy in prediction.关键词
多任务学习/转录因子结合位点/多数据域描述/核方法Key words
Multi-task learning/ Transcription factor binding sites/ Multiple data domain description/ Kernel methods引用本文复制引用
陈鸣,薛慧君,熊赟,朱扬勇..基于多数据域描述的转录因子结合位点识别[J].计算机应用与软件,2011,28(6):1-4,42,5.基金项目
国家自然基金项目(60903075) （60903075）
上海市重点学科项目(B114). （B114）
