iRNA-2OM: A Sequence-Based Predictor for Identifying 2'-O-Methylation Sites in Homo sapiens

2'-O-methylation plays an important biological role in gene expression. Owing to the explosive increase in genomic sequencing data, it is necessary to develop a method for quickly and efficiently identifying whether a sequence contains the 2'-O-methylation site. As an additional method to...

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Bibliographic Details
Published inJournal of computational biology Vol. 25; no. 11; p. 1266
Main Authors Yang, Hui, Lv, Hao, Ding, Hui, Chen, Wei, Lin, Hao
Format Journal Article
LanguageEnglish
Published United States 01.11.2018
Subjects
chemical property
Homo sapiens
PseKNC
RNA sequence
2′-O-methylation
Online AccessGet more information
ISSN1557-8666
DOI10.1089/cmb.2018.0004

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Summary:2'-O-methylation plays an important biological role in gene expression. Owing to the explosive increase in genomic sequencing data, it is necessary to develop a method for quickly and efficiently identifying whether a sequence contains the 2'-O-methylation site. As an additional method to the experimental technique, a computational method may help to identify 2'-O-methylation sites. In this study, based on the experimental 2'-O-methylation data of Homo sapiens, we proposed a support vector machine-based model to predict 2'-O-methylation sites in H. sapiens. In this model, the RNA sequences were encoded with the optimal features obtained from feature selection. In the fivefold cross-validation test, the accuracy reached 97.95%.
ISSN:1557-8666
DOI:10.1089/cmb.2018.0004