Literature DB >> 33604189

6mA-Pred: identifying DNA N6-methyladenine sites based on deep learning.

Qianfei Huang1, Wenyang Zhou2, Fei Guo1, Lei Xu3, Lichao Zhang4.   

Abstract

With the accumulation of data on 6mA modification sites, an increasing number of scholars have begun to focus on the identification of 6mA sites. Despite the recognized importance of 6mA sites, methods for their identification remain lacking, with most existing methods being aimed at their identification in individual species. In the present study, we aimed to develop an identification method suitable for multiple species. Based on previous research, we propose a method for 6mA site recognition. Our experiments prove that the proposed 6mA-Pred method is effective for identifying 6mA sites in genes from taxa such as rice, Mus musculus, and human. A series of experimental results show that 6mA-Pred is an excellent method. We provide the source code used in the study, which can be obtained from http://39.100.246.211:5004/6mA_Pred/.
© 2021 Huang et al.

Entities:  

Keywords:  6mA; Attention; LSTM

Year:  2021        PMID: 33604189      PMCID: PMC7866889          DOI: 10.7717/peerj.10813

Source DB:  PubMed          Journal:  PeerJ        ISSN: 2167-8359            Impact factor:   2.984


  58 in total

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  1 in total

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