iRNA-PseKNC(2methyl): Identify RNA 2′-O-methylation sites by convolution neural network and Chou's pseudo components

JOURNAL OF THEORETICAL BIOLOGY

卷:465

Article

Tahir, Muhammad^1,2  Tayara, Hilal¹  Chong, Kil To³ 

[1] Chonbuk Natl Univ, Dept Elect & Informat Engn, Jeonju 54896, South Korea

[2] Abdul Wali Khan Univ, Dept Comp Sci, Mardan 23200, South Korea

[3] Chonbuk Natl Univ, Adv Elect & Informat Res Ctr, Jeonju 54896, South Korea

关键词: Convolution neural network;    2 '-O-methylation;    RNA;    Deep learning;    CNN;    SVM;   

DOI  :  10.1016/j.jtbi.2018.12.034

来源: Elsevier

【 摘 要 】

The 2'-O-methylation transferase is involved in the process of 2'-O-methylation. In catalytic processes, the 2-hydroxy group of the ribose moiety of a nucleotide accept a methyl group. This methylation process is a post-transcriptional modification, which occurs in various cellular RNAs and plays a vital role in regulation of gene expressions at the post-transcriptional level. Through biochemical experiments 2'-O-methylation sites produce good results but these biochemical process and exploratory techniques are very expensive. Thus, it is required to develop a computational method to identify 2'-O-methylation sites. In this work, we proposed a simple and precise convolution neural network method namely: iRNA-PseKNC(2methyl) to identify 2'-O-methylation sites. The existing techniques use handcrafted features, while the proposed method automatically extracts the features of 2'-O-methylation using the proposed convolution neural network model. The proposed prediction iRNA-PseKNC(2methyl) method obtained 98.27% of accuracy, 96.29% of sensitivity, 100% of specificity, and 0.965 of MCC on Home sapiens dataset. The reported outcomes present that our proposed method obtained better outcomes than existing method in terms of all evaluation parameters. These outcomes show that iRNA-PseKNC(2methyl) method might be beneficial for the academic research and drug design. (C) 2018 The Authors. Published by Elsevier Ltd.

【 授权许可】

Free