Building a meta-predictor for MHC class II-binding peptides.
Building a meta-predictor for MHC class II-binding peptides.
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构建 MHC II 类结合肽的元预测器。
DOI：
10.1007/978-1-60327-118-9_26
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
Dai,Yang
中科院分区：
文献类型：
--
作者：
Huang,Lei;Karpenko,Oleksiy;Murugan,Naveen;Dai,Yang
II类主要组织相容性复合体(MHC) -肽结合的预测是一项具有挑战性的任务，因为结合肽的长度可变。已经开发了不同的计算方法；然而，每一种都有自己的优点和缺点。为了提供可靠的预测，重要的是设计一个系统，能够整合来自各种预测器的结果。在本章中，介绍了基于Naïve贝叶斯方法构建这种元预测器的过程。该系统是这样设计的，从任何数量的单个预测器获得的结果可以很容易地合并。这个元预测器可以让用户对预测更有信心。
Prediction of class II major histocompatibility complex (MHC)–peptide binding is a challenging task due to variable length of binding peptides. Different computational methods have been developed; however, each has its own strength and weakness. In order to provide reliable prediction, it is important to design a system that enables the integration of outcomes from various predictors. In this chapter, the procedure of building such a meta-predictor based on Naïve Bayesian approach is introduced. The system is designed in such a way that results obtained from any number of individual predictors can be easily incorporated. This meta-predictor is expected to give users more confidence in the prediction.