Statistical analysis of non-coding RNA data

With rapid progress in high-throughput genome technology, the study of noncoding RNA has arisen as a highly popular topic in biomedical research. Noncoding RNA plays fundamental roles in cell proliferation, cell differentiation and epigenetic regulation, and the study of noncoding RNA will yield nov...

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Vydáno v:Cancer letters Ročník 417; s. 161 - 167
Hlavní autoři: He, Qianchuan, Liu, Yang, Sun, Wei
Médium: Journal Article
Jazyk:angličtina
Vydáno: Ireland Elsevier B.V 28.03.2018
Elsevier Limited
Témata:
Animals
Annotations
Cell proliferation
Computational Biology - methods
Computer applications
Data analysis
Databases, Genetic
Deoxyribonucleic acid
DNA
DNA methylation
Gastric cancer
Gene expression
Gene Expression Regulation
Gene regulation
Genomes
Humans
Identification
Long noncoding RNA
Medical prognosis
Methods
MicroRNA
MicroRNAs
MicroRNAs - genetics
miRNA
Non-coding RNA
Noncoding RNA
Reviews
RNA, Long Noncoding - genetics
RNA, Untranslated - genetics
Statistical analysis
Statistical modeling
Statistics
Target prediction
Noncoding RNA
Statistical modeling
MicroRNA
Statistical analysis
Long noncoding RNA
Target prediction
ISSN:0304-3835, 1872-7980, 1872-7980
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Popis
Shrnutí:With rapid progress in high-throughput genome technology, the study of noncoding RNA has arisen as a highly popular topic in biomedical research. Noncoding RNA plays fundamental roles in cell proliferation, cell differentiation and epigenetic regulation, and the study of noncoding RNA will yield novel insights into gene regulation and provide new clues for disease treatment. However, due to the large volume and diverse functions of noncoding RNAs, the analysis of these RNAs has proved to be a challenging task. In this review, we review the commonly used computational tools for the identification of noncoding RNAs, and discuss popular statistical tools for their analysis. Due to the large body of noncoding RNA classes, we focus on the analysis of microRNA and long noncoding RNA, two of the most widely studied classes of noncoding RNAs. Specific examples are provided to show the context of the analysis. This review aims to provide up-to-date information on existing tools and methods for identifying and analyzing noncoding RNA.
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Equally contributed
ISSN:0304-3835
1872-7980
1872-7980
DOI:10.1016/j.canlet.2017.12.029