SVM based method for predicting HLA-DRB1*0401 binding peptides in an antigen sequence
SVM based method for predicting HLA-DRB1*0401 binding peptides in an antigen sequence
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DOI：
10.1093/bioinformatics/btg424
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发表时间：
2004-02-12
期刊：
影响因子：
5.8
通讯作者：
Raghava, GPS
中科院分区：
文献类型：
--
作者：
Bhasin, M;Raghava, GPS
预测与MHC II类等位基因HLA-DRB1(*)0401结合的肽可以有效减少鉴定辅助性T细胞表位所需的实验次数。本文介绍了基于支持向量机（SVM）的HLA-DRB1(*)0401结合肽抗原序列识别方法。SVM在由567个binder和等量的非binder组成的大型干净数据集上进行训练和测试。通过5倍交叉验证技术评估，该方法的准确度为86%。
Prediction of peptides binding with MHC class II allele HLA-DRB1(*)0401 can effectively reduce the number of experiments required for identifying helper T cell epitopes. This paper describes support vector machine (SVM) based method developed for identifying HLA-DRB1(*)0401 binding peptides in an antigenic sequence. SVM was trained and tested on large and clean data set consisting of 567 binders and equal number of non-binders. The accuracy of the method was 86% when evaluated through 5-fold cross-validation technique.