首页 | 本学科首页   官方微博 | 高级检索  
     检索      

PCA方法在蛋白质亚细胞定位中应用
引用本文:马军伟,史舵,顾宏,张杰.PCA方法在蛋白质亚细胞定位中应用[J].大连理工大学学报,2012,52(3):426-430.
作者姓名:马军伟  史舵  顾宏  张杰
作者单位:1. 大连理工大学控制科学与工程学院,辽宁大连116024/山西省电力公司电力通信中心,山西太原030001
2. 大连理工大学控制科学与工程学院,辽宁大连,116024
3. 安徽工业大学数理学院,安徽马鞍山,243002
摘    要:蛋白质的亚细胞定位与其生物功能密切相关,蛋白质数据库急剧膨胀,迫切需要设计出功能强大的高吞吐量的算法来预测蛋白质的亚细胞位置.许多预测工具都是基于伪氨基酸组成构建而成,应用一种数据分析方法——主成分分析(PCA)法,确定能反映序列次序效应的最优λ值.首先让λ取最大以包含尽可能多的序列次序信息,然后利用主成分分析法提取关键主特征.实验结果表明此方法能解决确定最优λ值困难的问题,且性能优于已有的预测工具.

关 键 词:蛋白质亚细胞定位  主成分分析  伪氨基酸组成  k近邻分类器  BP神经网络

Application of PCA method to predicting protein subcellular location
MA Junwei,SHI Duo,GU Hong,ZHANG Jie.Application of PCA method to predicting protein subcellular location[J].Journal of Dalian University of Technology,2012,52(3):426-430.
Authors:MA Junwei  SHI Duo  GU Hong  ZHANG Jie
Institution:1.School of Control Science and Engineering,Dalian University of Technology,Dalian 116024,China;2.Center of Electric Power Communication,Shanxi Electric Power Company,Taiyuan 030001,China;3.School of Mathematics & Physics,Anhui University of Technology,Ma′anshan 243002,China)
Abstract:The location of a protein subcellular is closely correlated with its biological function.With the rapid expansion of protein databases,it is very important to design a powerful high-throughput algorithm for predicting protein subcellular location.Many prediction tools have been designed based on the pseudo-amino acid composition,and a data analysis method,principal component analysis(PCA) method,is applied to determining in advance the optimal value of λ which reflects sequence order effects.Firstly,the parameter λ is set to the maximum to contain more sequence order information;then,PCA is employed to extract the essential features.Experimental results show that the proposed method solves the above problem,and its performance is better than those of other predictors.
Keywords:protein subcellular location  principal component analysis  pseudo-amino acid composition  k-NN classifier  BP neural network
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《大连理工大学学报》浏览原始摘要信息
点击此处可从《大连理工大学学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号