MM-6mAPred：基于马尔可夫模型识别 DNA N6-甲基腺嘌呤位点。

MM-6mAPred: identifying DNA N6-methyladenine sites based on Markov model.

机构信息

Department of Statistics, The Chinese University of Hong Kong, Sha Tin, Hong Kong.

State Key Laboratory of Rice Biology and Ministry of Agricultural and Rural Affairs, Key Laboratory of Molecular Biology of Crop Pathogens and Insect Pests, Institute of Insect Sciences, Zhejiang University, Hangzhou 310058, China.

出版信息

Bioinformatics. 2020 Jan 15;36(2):388-392. doi: 10.1093/bioinformatics/btz556.

DOI:10.1093/bioinformatics/btz556

PMID:31297537

Abstract

MOTIVATION

Recent studies have shown that DNA N6-methyladenine (6mA) plays an important role in epigenetic modification of eukaryotic organisms. It has been found that 6mA is closely related to embryonic development, stress response and so on. Developing a new algorithm to quickly and accurately identify 6mA sites in genomes is important for explore their biological functions.

RESULTS

In this paper, we proposed a new classification method called MM-6mAPred based on a Markov model which makes use of the transition probability between adjacent nucleotides to identify 6mA site. The sensitivity and specificity of our method are 89.32% and 90.11%, respectively. The overall accuracy of our method is 89.72%, which is 6.59% higher than that of the previous method i6mA-Pred. It indicated that, compared with the 41 nucleotide chemical properties used by i6mA-Pred, the transition probability between adjacent nucleotides can capture more discriminant sequence information.

AVAILABILITY AND IMPLEMENTATION

The web server of MM-6mAPred is freely accessible at http://www.insect-genome.com/MM-6mAPred/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

动机

最近的研究表明，DNA N6-甲基腺嘌呤（6mA）在真核生物的表观遗传修饰中发挥着重要作用。已经发现 6mA 与胚胎发育、应激反应等密切相关。开发一种新的算法来快速准确地识别基因组中的 6mA 位点，对于探索其生物学功能至关重要。

结果

本文提出了一种新的分类方法，称为 MM-6mAPred，它基于马尔可夫模型，利用相邻核苷酸之间的转移概率来识别 6mA 位点。我们的方法的灵敏度和特异性分别为 89.32%和 90.11%。我们的方法的总体准确性为 89.72%，比之前的 i6mA-Pred 方法高 6.59%。这表明，与 i6mA-Pred 所使用的 41 个核苷酸化学性质相比，相邻核苷酸之间的转移概率可以捕获更多的区分序列信息。