EPSVR and EPMeta: prediction of antigenic epitopes using support vector regression and multiple server results.
EPSVR and EPMeta: prediction of antigenic epitopes using support vector regression and multiple server results.
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DOI：
10.1186/1471-2105-11-381
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发表时间：
2010-07-16
影响因子：
3
通讯作者：
Zhang C
中科院分区：
文献类型：
--
作者：
Liang S;Zheng D;Standley DM;Yao B;Zacharias M;Zhang C
抗原表位的准确预测对于免疫学研究和医学应用具有重要意义，但它仍然是生物信息学中的一个待解决的问题。不连续表位的情况甚至更糟-目前只有少数不连续表位预测服务器可用，尽管不连续肽构成所有B细胞抗原表位的大部分。抗原-抗体复合物的少量结构限制了可靠的不连续表位预测方法的开发和用于评估开发的方法的无偏基准。在这项工作中，我们提出了两个新的服务器应用程序的不连续表位预测：EPSVR和EPMETA，其中EPMETA是一个Meta服务器。EPSVR、EPMETA和数据集可在http://sysbio.unl.edu/services上获得。用于不连续表位预测的服务器应用程序EPSVR使用支持向量回归（SVR）方法来整合六个评分项。此外，我们将EPSVR与五个现有的表位预测服务器相结合，构建EPMETA。所有方法都通过我们策划的独立测试集进行基准测试，其中所有抗原与抗体没有复杂的结构，并且通过各种生化实验鉴定其表位。EPSVR的受试者工作特征曲线下面积（AUC）为0.597，高于任何其他现有的单一服务器，EPMETA的性能优于任何单一服务器-AUC为0.638，显著高于PEPITO和Disctope（p值< 0.05）。
Accurate prediction of antigenic epitopes is important for immunologic research and medical applications, but it is still an open problem in bioinformatics. The case for discontinuous epitopes is even worse - currently there are only a few discontinuous epitope prediction servers available, though discontinuous peptides constitute the majority of all B-cell antigenic epitopes. The small number of structures for antigen-antibody complexes limits the development of reliable discontinuous epitope prediction methods and an unbiased benchmark to evaluate developed methods. In this work, we present two novel server applications for discontinuous epitope prediction: EPSVR and EPMeta, where EPMeta is a meta server. EPSVR, EPMeta, and datasets are available at http://sysbio.unl.edu/services. The server application for discontinuous epitope prediction, EPSVR, uses a Support Vector Regression (SVR) method to integrate six scoring terms. Furthermore, we combined EPSVR with five existing epitope prediction servers to construct EPMeta. All methods were benchmarked by our curated independent test set, in which all antigens had no complex structures with the antibody, and their epitopes were identified by various biochemical experiments. The area under the receiver operating characteristic curve (AUC) of EPSVR was 0.597, higher than that of any other existing single server, and EPMeta had a better performance than any single server - with an AUC of 0.638, significantly higher than PEPITO and Disctope (p-value < 0.05).
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发表时间：
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期刊：
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影响因子：
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