Protein secondary structural classes prediction based on OET-KNN modeling

doi:10.3778/j.issn.1002-8331.2008.29.058

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (29): 204-206.DOI: 10.3778/j.issn.1002-8331.2008.29.058

• 工程与应用 • Previous Articles Next Articles

Protein secondary structural classes prediction based on OET-KNN modeling

QIU Wang-ren,XIAO Xuan,LIN Wei-zhong

Information Engineering School，Jingdezhen Ceramic Institute，Jingdezhen，Jiangxi 333403，China

Received:2008-04-14 Revised:2008-07-04 Online:2008-10-11 Published:2008-10-11
Contact: QIU Wang-ren

基于OET-KNN算法的蛋白质二级结构类型预测

邱望仁,肖绚,林卫中

景德镇陶瓷学院信息工程学院，江西景德镇 333403

通讯作者: 邱望仁

Abstract

Abstract: Protein secondary structure prediction is the hot of bioinformatics.In this paper，a novel method based on optimal evidence-theoretic K nearest neighbor（OET-KNN） algorithm has been introduced，in which，based on encoding the amino acid sequence into digital signals，the pseudo amino acid composition is incorporated with the complexity through the LZ’s algorithm.The result of these pseudo-amino acids shows that the prediction success rate is improved.

Key words: protein, predict protein secondary structural classes, optimal evidence-theoretic K nearest neighbor（OET-KNN）

摘要： 蛋白质二级结构类型预测是当今生物信息学研究的热点之一。利用氨基酸数字编码模型将氨基酸序列转换成数字信号，根据LZ复杂度的算法计算了氨基酸的伪氨基酸成分，再对伪氨基酸成分用OET-KNN算法进行分类预测。Jackknife测试结果表明该算法能使得预测成功率有较大的提高。

关键词: 蛋白质, 二级结构型预测, K-近邻算法

QIU Wang-ren,XIAO Xuan,LIN Wei-zhong. Protein secondary structural classes prediction based on OET-KNN modeling[J]. Computer Engineering and Applications, 2008, 44(29): 204-206.

邱望仁,肖绚,林卫中

. 基于OET-KNN算法的蛋白质二级结构类型预测[J]. 计算机工程与应用, 2008, 44(29): 204-206.

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Protein secondary structural classes prediction based on OET-KNN modeling

基于OET-KNN算法的蛋白质二级结构类型预测

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