Liu Zi, Xiao Xuan, Qiu Wang-Ren, Chou Kuo-Chen
Computer Department, Jing-De-Zhen Ceramic Institute, Jing-De-Zhen 333403, China.
Computer Department, Jing-De-Zhen Ceramic Institute, Jing-De-Zhen 333403, China; Gordon Life Science Institute, Boston, MA 02478, USA.
Anal Biochem. 2015 Apr 1;474:69-77. doi: 10.1016/j.ab.2014.12.009. Epub 2015 Jan 14.
Predominantly occurring on cytosine, DNA methylation is a process by which cells can modify their DNAs to change the expression of gene products. It plays very important roles in life development but also in forming nearly all types of cancer. Therefore, knowledge of DNA methylation sites is significant for both basic research and drug development. Given an uncharacterized DNA sequence containing many cytosine residues, which one can be methylated and which one cannot? With the avalanche of DNA sequences generated during the postgenomic age, it is highly desired to develop computational methods for accurately identifying the methylation sites in DNA. Using the trinucleotide composition, pseudo amino acid components, and a dataset-optimizing technique, we have developed a new predictor called "iDNA-Methyl" that has achieved remarkably higher success rates in identifying the DNA methylation sites than the existing predictors. A user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/iDNA-Methyl, where users can easily get their desired results. We anticipate that the web-server predictor will become a very useful high-throughput tool for basic research and drug development and that the novel approach and technique can also be used to investigate many other DNA-related problems and genome analysis.
DNA甲基化主要发生在胞嘧啶上,是细胞修饰其DNA以改变基因产物表达的过程。它在生命发育中起着非常重要的作用,同时也与几乎所有类型癌症的形成有关。因此,了解DNA甲基化位点对基础研究和药物开发都具有重要意义。给定一个含有许多胞嘧啶残基的未表征DNA序列,哪些可以被甲基化,哪些不能?在后基因组时代产生了大量的DNA序列,因此迫切需要开发计算方法来准确识别DNA中的甲基化位点。利用三核苷酸组成、伪氨基酸组分和数据集优化技术,我们开发了一种名为“iDNA-Methyl”的新预测器,在识别DNA甲基化位点方面比现有预测器取得了显著更高的成功率。已在http://www.jci-bioinfo.cn/iDNA-Methyl建立了一个用户友好的新预测器网络服务器,用户可以轻松获得他们想要的结果。我们预计,该网络服务器预测器将成为基础研究和药物开发中非常有用的高通量工具,并且这种新方法和技术还可用于研究许多其他与DNA相关的问题和基因组分析。