Prediction of methylated CpGs in DNA sequences using a support vector machine
Prediction of methylated CpGs in DNA sequences using a support vector machine
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DOI：
10.1016/j.febslet.2005.07.002
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发表时间：
2005-08-15
期刊：
影响因子：
3.5
通讯作者：
Reche, PA
中科院分区：
文献类型：
--
作者：
Bhasin, M;Zhang, H;Reche, PA
DNA甲基化在基因表达调控中起着关键作用。最常见的DNA修饰类型包括CpG二核苷酸中胞嘧啶的甲基化。目前，还没有一种方法可以预测DNA甲基化位点。因此，在这项研究中，我们开发了一种基于支持向量机（SVM）的方法来预测CpG二核苷酸中的胞嘧啶甲基化。最初，从人类数据开发SVM模块用于预测人类特异性甲基化位点。当使用5倍交叉验证进行评价时，该模块分别实现了0.501和0.814的MCC和AUC。这个基于SVM的模块的性能优于使用替代机器学习和统计算法（包括人工神经网络，贝叶斯统计和决策树）构建的分类器。还基于哺乳动物和脊椎动物特异性甲基化模式开发了其他SVM模块。基于人类甲基化模式的SVM模块用于甲基化位点的全基因组分析。该分析表明，与人类基因的外显子和内含子区域相比，UTR中甲基化CpG的百分比更高。该方法可在http://bio.dfci.harvard.edu/Methylator/上以Methylator的名称在线获得以供公众使用。(c)2005年欧洲生物化学学会联合会。由Elsevier B.V.出版，版权所有。
DNA methylation plays a key role in the regulation of gene expression. The most common type of DNA modification consists of the methylation of cytosine in the CpG dinucleotide. At the present time, there is no method available for the prediction of DNA methylation sites. Therefore, in this study we have developed a support vector machine (SVM)-based method for the prediction of cytosine methylation in CpG dinucleotides. Initially a SVM module was developed from human data for the prediction of human-specific methylation sites. This module achieved a MCC and AUC of 0.501 and 0.814, respectively, when evaluated using a 5-fold cross-validation. The performance of this SVM-based module was better than the classifiers built using alternative machine learning and statistical algorithms including artificial neural networks, Bayesian statistics, and decision trees. Additional SVM modules were also developed based on mammalian- and vertebrate-specific methylation patterns. The SVM module based on human methylation patterns was used for genome-wide analysis of methylation sites. This analysis demonstrated that the percentage of methylated CpGs is higher in UTRs as compared to exonic and intronic regions of human genes. This method is available on line for public use under the name of Methylator at http://bio.dfci.harvard.edu/Methylator/. (c) 2005 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.