结合支持向量机和贝叶斯方法进行蛋白质二级结构预测
결합지지향량궤화패협사방법진행단백질이급결구예측
Protein Secondary Structure Prediction Using SVM with Bayesian Method
  • 万方数据
    生物信息学 생물신식학
    BIOINFORMATICS
    2010年 1期 75-77,81 ,共4页

    王宝文%王水星%刘文远%于家新

    왕보문%왕수성%류문원%우가신

    蛋白质二级结构%支持向量机%贝叶斯方法 蛋白質二級結構%支持嚮量機%貝葉斯方法
    단백질이급결구%지지향량궤%패협사방법
    Protein secondary structures%Support vector machine%Bayesian Method
    组建一个分两个阶段的分类器来进行蛋白质二级结构预测.第一阶段由支持向量机分类器组成,在第二阶段中使用第一阶段已预测的结果来进行贝叶斯判别.预测性能的改进表明了结合支持向量机和贝叶斯方法预测性能优越于单独使用支持向量机的预测性能.同时也证明残基在形成二级结构时是相互影响的.
    조건일개분량개계단적분류기래진행단백질이급결구예측.제일계단유지지향량궤분류기조성,재제이계단중사용제일계단이예측적결과래진행패협사판별.예측성능적개진표명료결합지지향량궤화패협사방법예측성능우월우단독사용지지향량궤적예측성능.동시야증명잔기재형성이급결구시시상호영향적.
    A two stage predictor is constructed to predict protein secondary structures. The first stage consists of one predictor based on the support vector machine. Bayesian discrimination is used at the second stage by considering the predicted labels of neighbor residues.The improvement of prediction performances indicates that this method outperforms the predictors based on SVM algorithm alone. At the same time,it proves that the residues are interactional when they constitute protein secondary structures.
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