Bioinformatics approaches for deciphering the epitranscriptome: Recent progress and emerging topics
Author(s) -
Lian Liu,
Bowen Song,
Jiani Ma,
Yi Song,
Song-Yao Zhang,
Yujiao Tang,
Xiangyu Wu,
Zhen Wei,
Kunqi Chen,
Jionglong Su,
Rong Rong,
Zhi-Liang Lu,
João Pedro de Magalhães,
Daniel J. Rigden,
Lin Zhang,
ShaoWu Zhang,
Yufei Huang,
Xiujuan Lei,
Hui Liu,
Jia Meng
Publication year - 2020
Publication title -
computational and structural biotechnology journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.908
H-Index - 45
ISSN - 2001-0370
DOI - 10.1016/j.csbj.2020.06.010
Subject(s) - computational biology , rna , transcriptome , annotation , inference , computer science , profiling (computer programming) , biology , bioinformatics , data science , gene , genetics , gene expression , artificial intelligence , operating system
Post-transcriptional RNA modification occurs on all types of RNA and plays a vital role in regulating every aspect of RNA function. Thanks to the development of high-throughput sequencing technologies, transcriptome-wide profiling of RNA modifications has been made possible. With the accumulation of a large number of high-throughput datasets, bioinformatics approaches have become increasing critical for unraveling the epitranscriptome. We review here the recent progress in bioinformatics approaches for deciphering the epitranscriptomes, including epitranscriptome data analysis techniques, RNA modification databases, disease-association inference, general functional annotation, and studies on RNA modification site prediction. We also discuss the limitations of existing approaches and offer some future perspectives.
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