%0 Journal Article
%T Identification of 5’UTR Splice Sites In Human Gene Based On Support Vector Machine<br>基于支持向量机的人类5’非翻译区剪接位点识别
%A YAN Chun
%A DU Yao-hua
%A GAO Qing-bin
%A WANG Zheng-zhi
%A <br>晏春
%A 杜耀华
%A 高青斌
%A 王正志
%J 生物物理学报
%D 2005
%I 
%X Identification of splice sites in non-coding regions of genes is one of the most challenging aspects of gene structure recognition, especially the identification of splice sites embedded in human 5' untranslated regions (UTRs). Different from the conventional splice sites identification, there is no transition from coding to non-coding in 5'UTRs, so conventional splice sites prediction methods perform poorly in UTRs. In this paper, support vector machines was used to identify 5'UTRs splice sites. To increase recognition accuracy, the measurement of matrix similarity was used as the criterion of parameters selection. By doing this, apropos parameters were achieved quickly and simply, thereby improved the identification performance. Experiment results showed that 5'UTRs splice sites can be identified well based on SVM with the selection of parameters.
%K 5'UTRs splice sites
%K Identification
%K Support vector machine
%K Kernel
%K Parameter selection<br>5’非翻译区剪接位点
%K 识别
%K 支持向量机
%K 核函数
%K 参数选择
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=90BA3D13E7F3BC869AC96FB3DA594E3FE34FBF7B8BC0E591&jid=E0C9D9BBED813D6674AC13E942EAC86D&aid=92F65D8923A08D23&yid=2DD7160C83D0ACED&vid=659D3B06EBF534A7&iid=E158A972A605785F&sid=03E56C113B4E5A88&eid=334C61CAF4C8EF4E&journal_id=1000-6737&journal_name=生物物理学报&referenced_num=4&reference_num=12