A review of methods for predicting DNA N6-methyladenine sites

Author:

Han Ke12ORCID,Wang Jianchun1,Wang Yu1,Zhang Lei1,Yu Mengyao1,Xie Fang1,Zheng Dequan1,Xu Yaoqun1,Ding Yijie3,Wan Jie4

Affiliation:

1. School of Computer and Information Engineering, Heilongjiang Provincial Key Laboratory of Electronic Commerce and Information Processing, Harbin University of Commerce , Harbin, 150028 , China

2. College of Pharmacy, Harbin University of Commerce , Harbin, 150076 , China

3. Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China , Quzhou, 324000 , China

4. Laboratory for Space Environment and Physical Sciences, Harbin Institute of Technology , Harbin, 150001 , China

Abstract

AbstractDeoxyribonucleic acid(DNA) N6-methyladenine plays a vital role in various biological processes, and the accurate identification of its site can provide a more comprehensive understanding of its biological effects. There are several methods for 6mA site prediction. With the continuous development of technology, traditional techniques with the high costs and low efficiencies are gradually being replaced by computer methods. Computer methods that are widely used can be divided into two categories: traditional machine learning and deep learning methods. We first list some existing experimental methods for predicting the 6mA site, then analyze the general process from sequence input to results in computer methods and review existing model architectures. Finally, the results were summarized and compared to facilitate subsequent researchers in choosing the most suitable method for their work.

Funder

NSFC

Natural Science Foundation of Heilongjiang Province

Municipal Government of Quzhou

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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