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iRNAm5C-PseDNC:通过将理化性质融入伪二核苷酸组成来识别RNA 5-甲基胞嘧啶位点

iRNAm5C-PseDNC: identifying RNA 5-methylcytosine sites by incorporating physical-chemical properties into pseudo dinucleotide composition.

作者信息

Qiu Wang-Ren, Jiang Shi-Yu, Xu Zhao-Chun, Xiao Xuan, Chou Kuo-Chen

机构信息

Department of Computer Science and Bond Life Science Center, University of Missouri, Columbia, MO, USA.

Computer Department, Jingdezhen Ceramic Institute, Jingdezhen, China.

出版信息

Oncotarget. 2017 Jun 20;8(25):41178-41188. doi: 10.18632/oncotarget.17104.

Abstract

Occurring at cytosine (C) of RNA, 5-methylcytosine (m5C) is an important post-transcriptional modification (PTCM). The modification plays significant roles in biological processes by regulating RNA metabolism in both eukaryotes and prokaryotes. It may also, however, cause cancers and other major diseases. Given an uncharacterized RNA sequence that contains many C residues, can we identify which one of them can be of m5C modification, and which one cannot? It is no doubt a crucial problem, particularly with the explosive growth of RNA sequences in the postgenomic age. Unfortunately, so far no user-friendly web-server whatsoever has been developed to address such a problem. To meet the increasingly high demand from most experimental scientists working in the area of drug development, we have developed a new predictor called iRNAm5C-PseDNC by incorporating ten types of physical-chemical properties into pseudo dinucleotide composition via the auto/cross-covariance approach. Rigorous jackknife tests show that its anticipated accuracy is quite high. For most experimental scientists' convenience, a user-friendly web-server for the predictor has been provided at http://www.jci-bioinfo.cn/iRNAm5C-PseDNC along with a step-by-step user guide, by which users can easily obtain their desired results without the need to go through the complicated mathematical equations involved. It has not escaped our notice that the approach presented here can also be used to deal with many other problems in genome analysis.

摘要

5-甲基胞嘧啶(m5C)发生于RNA的胞嘧啶(C)位点,是一种重要的转录后修饰(PTCM)。这种修饰通过调节真核生物和原核生物的RNA代谢,在生物过程中发挥着重要作用。然而,它也可能引发癌症和其他重大疾病。对于一个包含许多C残基的未表征RNA序列,我们能否识别出其中哪些可以进行m5C修饰,哪些不能?这无疑是一个关键问题,尤其是在后基因组时代RNA序列呈爆炸式增长的情况下。不幸的是,到目前为止,尚未开发出任何用户友好的网络服务器来解决此类问题。为了满足药物研发领域大多数实验科学家日益增长的高需求,我们通过自相关/互协方差方法将十种物理化学性质纳入伪二核苷酸组成,开发了一种名为iRNAm5C-PseDNC的新预测器。严格的留一法测试表明,其预期准确率相当高。为方便大多数实验科学家使用,在http://www.jci-bioinfo.cn/iRNAm5C-PseDNC提供了一个用户友好的预测器网络服务器以及一份详细的用户指南,通过该指南,用户无需推导复杂的数学公式就能轻松获得所需结果。我们也注意到,这里提出的方法也可用于处理基因组分析中的许多其他问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2892/5522291/e54df0b55b93/oncotarget-08-41178-g001.jpg

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