Disease-Associated Circular RNAs: From Biology to Computational Identification
Joint Authors
Kui, Ling
Tang, Min
Lu, Guanyi
Chen, Wenqiang
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-21, 21 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-18
Country of Publication
Egypt
No. of Pages
21
Main Subjects
Abstract EN
Circular RNAs (circRNAs) are endogenous RNAs with a covalently closed continuous loop, generated through various backsplicing events of pre-mRNA.
An accumulating number of studies have shown that circRNAs are potential biomarkers for major human diseases such as cancer and Alzheimer’s disease.
Thus, identification and prediction of human disease-associated circRNAs are of significant importance.
To this end, a computational analysis-assisted strategy is indispensable to detect, verify, and quantify circRNAs for downstream applications.
In this review, we briefly introduce the biology of circRNAs, including the biogenesis, characteristics, and biological functions.
In addition, we outline about 30 recent bioinformatic analysis tools that are publicly available for circRNA study.
Principles for applying these computational strategies and considerations will be briefly discussed.
Lastly, we give a complete survey on more than 20 key computational databases that are frequently used.
To our knowledge, this is the most complete and updated summary on publicly available circRNA resources.
In conclusion, this review summarizes key aspects of circRNA biology and outlines key computational strategies that will facilitate the genome-wide identification and prediction of circRNAs.
American Psychological Association (APA)
Tang, Min& Kui, Ling& Lu, Guanyi& Chen, Wenqiang. 2020. Disease-Associated Circular RNAs: From Biology to Computational Identification. BioMed Research International،Vol. 2020, no. 2020, pp.1-21.
https://search.emarefa.net/detail/BIM-1136212
Modern Language Association (MLA)
Tang, Min…[et al.]. Disease-Associated Circular RNAs: From Biology to Computational Identification. BioMed Research International No. 2020 (2020), pp.1-21.
https://search.emarefa.net/detail/BIM-1136212
American Medical Association (AMA)
Tang, Min& Kui, Ling& Lu, Guanyi& Chen, Wenqiang. Disease-Associated Circular RNAs: From Biology to Computational Identification. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-21.
https://search.emarefa.net/detail/BIM-1136212
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1136212