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基于添加功能位点信息的组合向量预测β-发夹模体 被引量：2

Predicting β-Hairpins Based on Combined Vector of Adding Information of Function Motif
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摘要 一条蛋白质序列通常是用多种特征来表达的,因此使用简单的特征参数对蛋白质结构进行预测,得到的效果往往不尽人意。在前人使用过的预测β-发夹的特征参数基础上,将功能位点信息添加到特征参数中,共同输入到支持向量机和随机森林两种算法,对4070条非冗余的蛋白质链中的β-发夹模体进行了预测。支持向量机算法得到的预测精度80.2%,相关系数0.60;随机森林算法得到的预测精度83.3%,相关系数0.66。 A protein sequence is usually expressed in various features. For this reason, prediction the protein structure with simple feature parameters is unsatisfactory. The information of function is added to the feature parameters of used. The β - hairpins are predicted in 4070 non - redundant protein chains by using both algorithms with support vector machine and Random Forest, and obtained the overall prediction accuracy of 80.2% and 83.3%, with the Matthews Correlation Coefficient values of 0. 60 and 0. 66 respectively.
作者 贾少春 胡秀珍
机构地区 内蒙古工业大学理学院
出处 《内蒙古工业大学学报（自然科学版）》 2012年第3期1-9,共9页 Journal of Inner Mongolia University of Technology：Natural Science Edition
基金 国家自然科学基金资助项目(30960090)
关键词 Β-发夹模体 随机森林算法 预测的二级结构信息 自相关函数 功能位点信息 β-hairpin motif Random forest algorithm Information of predictive secondary structure autocorrelation function Information of function site.
分类号 O175 [理学—基础数学]
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参考文献29

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二级参考文献56

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共引文献22

同被引文献28

  • 1杨科利,李前忠,林昊.预测酵母(Yeast)基因转录因子结合位点[J].内蒙古大学学报（自然科学版）,2006,37(5):524-530. 被引量：16
  • 2袁敏,胡秀珍.随机森林方法预测膜蛋白类型[J].生物物理学.2009,5:349-355.
  • 3Kuhn M, Meiler J,Baker D. Strand - Loop - Strand Motifs:Prediction of Hairpins and Diverging Turns in Proteins [ J ]. PRO- TEINS : Structure, Function, Bioinformatics, 2004,54 (2) : 282 - 288.
  • 4Wintjens R T, Rooman M J, Wodak S J. Automatic classification and analysis of alpha alpha - Turn Motifs in Proteins [ J ]. Jour- nal of Molecular Biology, 1996,255 ( 1 ) :235 - 253.
  • 5Jones DT. Protein secondary structure prediction based on position- specific scoring matrices[ J ]. J. Mol. Biol, 1999,292 (2) : 195 - 202.
  • 6Cruz X, Hutchinson E G, Shepherd A. Toward predicting protein topology : An approach to identifying β hairpins [ J ]. Proceed- ings of the National Academy Sciences of the USA ,2002,99 (17) :11157 -11162.
  • 7Kumar M, Bhasin M, Natt N K, etc. BhairPred : prediction ofβ - hairpins in a protein from multiple alignment information using ANN and SVM techniques [ J ]. Nucleic Acids Research ( Web - server - Issue), 2005 ( 33 ) : 154 - 159.
  • 8Hu XZ, Li QZ. Prediction of the β -hairpins in Proteins Using Support Vector Machine [ J ]. Protein J,2008,27 (2) :115 - 122.
  • 9Hu XZ, Li QZ ,Wang CL. Recognition of β-hairpin motifs in proteins by using the composite vector[ J]. Amino. Acids ,2010, 38(3) :915 -921.
  • 10Oliva A,Bates P A,Querol E,et al. An Automated Classification of the Structure of Protein Loops[ J]. J. Mol. Biol, 1997,266 (4) :814 -830.

引证文献2

内蒙古工业大学学报（自然科学版）
2012年 第3期

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