Cong Pian1,2, Guangle Zhang3, Fei Li2, Xiaodan Fan1. 1. Department of Statistics, The Chinese University of Hong Kong, Sha Tin, Hong Kong. 2. 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. 3. Binjiang College, Nanjing University of Information Science and Technology, Jiangsu, China.
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.
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.
Authors: Anthony Mackitz Dzisoo; Juanjuan Kang; Pengcheng Yao; Benjamin Klugah-Brown; Birga Anteneh Mengesha; Jian Huang Journal: Biomed Res Int Date: 2020-06-02 Impact factor: 3.411