i4mC-ROSE, a bioinformatics tool for the identification of DNA N4-methylcytosine sites in the Rosaceae genome

被引:75
作者
Hasan, Md Mehedi [1 ,2 ]
Manavalan, Balachandran [3 ]
Khatun, Mst Shamima [1 ]
Kurata, Hiroyuki [1 ,4 ]
机构
[1] Kyushu Inst Technol, Dept Biosci & Bioinformat, Chiyoda Ku, 680-4 Kawazu, Iizuka, Fukuoka 8208502, Japan
[2] Japan Soc Promot Sci, Chiyoda Ku, 5-3-1 Kojimachi, Tokyo 1020083, Japan
[3] Ajou Univ, Sch Med, Dept Physiol, Suwon 443380, South Korea
[4] Kyushu Inst Technol, Biomed Informat R&D Ctr, 680-4 Kawazu, Iizuka, Fukuoka 8208502, Japan
关键词
N4-methylcytosine site; DNA methylation; Sequence encoding; Machine learning; Linear regression; METHYLATION; PREDICTION; METHYLTRANSFERASES; DIVERSIFICATION; SPECIFICITY; PATTERNS; PLANTS;
D O I
10.1016/j.ijbiomac.2019.12.009
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
One of the most important epigenetic modifications is N4-methylcytosine, which regulates many biological processes including DNA replication and chromosome stability. Identification of N4-methylcytosine sites is pivotal to understand specific biological functions. Herein, we developed the first bioinformatics tool called i4mC-ROSE for identifying N4-methylcytosine sites in the genomes of Fragazia vesca and Rosa chinensis in the Rosaceae, which utilizes a random forest classifier with six encoding methods that cover various aspects of DNA sequence information. The i4mC-ROSE predictor achieves area under the curve scores of 0.883 and 0.889 for the two genomes during cross-validation. Moreover, the i4mC-ROSE outperforms other classifiers tested in this study when objectively evaluated on the independent datasets. The proposed i4mC-ROSE tool can serve users demand for the prediction of 4mC sites in the Rosaceae genome. The i4mC-ROSE predictor and utilized datasets are publicly accessible at http://kurata14.bio.kyutech.ac.jp/i4mC-ROSE/. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码:752 / 758
页数:7
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