SoftVoting6mA: An improved ensemble-based method for predicting DNA N6-methyladenine sites in cross-species genomes

被引：1

作者：

Yin Z. ^{[1
]}

Lyu J. ^{[1
]}

Zhang G. ^{[1
]}

Huang X. ^{[1
]}

Ma Q. ^{[2
,3
]}

Jiang J. ^{[1
]}

机构：

[1] College of Information Science and Engineering, Shaoyang University, Shaoyang

[2] College of Information Science and Engineering, Hohai University, Nanjing

[3] Faculty of Information Technology, University of Jyvaskyla, Jyvaskyla

来源：

Mathematical Biosciences and Engineering | 2024年 / 21卷 / 03期

关键词：

convolution neural network; cross-species; DNA N6-methyladenine; feature fusion; soft voting; webserver;

D O I：

10.3934/mbe.2024169

中图分类号：

学科分类号：

摘要：

The DNA N6-methyladenine (6mA) is an epigenetic modification, which plays a pivotal role in biological processes encompassing gene expression, DNA replication, repair, and recombination. Therefore, the precise identification of 6mA sites is fundamental for better understanding its function, but challenging. We proposed an improved ensemble-based method for predicting DNA N6-methyladenine sites in cross-species genomes called SoftVoting6mA. The SoftVoting6mA selected four (electron–ion-interaction pseudo potential, One-hot encoding, Kmer, and pseudo dinucleotide composition) codes from 15 types of encoding to represent DNA sequences by comparing their performances. Similarly, the SoftVoting6mA combined four learning algorithms using the soft voting strategy. The 5-fold cross-validation and the independent tests showed that SoftVoting6mA reached the state-of-the-art performance. To enhance accessibility, a user-friendly web server is provided at http://www.biolscience.cn/SoftVoting6mA/. © 2024 the Author(s).

引用

页码：3798 / 3815

页数：17

共 40 条

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