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	A new classification method for human gene splice site prediction
	Wei, Dan ; Zhuang, Wei ; Jiang, Qingshan ; Wei, Yanjie ; Jiang QS(姜青山)
	2012
关键词	Encoding (symbols) Feature extraction Forecasting Genetic engineering Information science Support vector machines
英文摘要	Conference Name:1st International Conference on Health Information Science, HIS 2012. Conference Address: Beijing, China. Time:April 8, 2012 - April 10, 2012.; GUCAS-VU Joint Lab for Social Computing and E-Health Research; Hebei University of Engineering; Nanjing University of Finance and Economics; National Science Foundation of China; Victoria University; National Natural Science Foundation of China; Human splicing site prediction is important for identifying the complete structure of genes in Human genomes. Machine learning method is capable of distinguishing the different splice sites in genes. For machine learning method, feature extraction is a key step in dealing with the problem of splicing site identification. Encoding schema is a widely used method to encode gene sequences by feature vectors. However, this method ignores the information of the period-3 behavior of the splice sites and sequential information in the sequence. In this paper, a new feature extraction method, based on orthogonal encoding, codon usage and the sequential information, is proposed to map splice site sequences into feature vectors. Classification is performed using a Support Vector Machine (SVM) method. The experimental results show that the new method can predict human splice sites with high classification accuracy. 漏 2012 Springer-Verlag.
语种	英语
出处	http://dx.doi.org/10.1007/978-3-642-29361-0_16
出版者	Springer Verlag
内容类型	其他
源URL	[http://dspace.xmu.edu.cn/handle/2288/85773]
专题	软件学院－会议论文
推荐引用方式 GB/T 7714	Wei, Dan,Zhuang, Wei,Jiang, Qingshan,et al. A new classification method for human gene splice site prediction. 2012-01-01.

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