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cncRNAdb: a manually curated resource of experimentally supported RNAs with both protein-coding and noncoding
Yan Huang1, Jing Wang2, Yue Zhao3
1Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan 528308, China.
Nucleic Acids Research
|October 3, 2020
Summary
A new database, cncRNAdb, has been developed to catalog dual-function RNAs (cncRNAs) that possess both coding and noncoding functions. This resource aids in the study and manipulation of these versatile RNA molecules.
Area of Science:
- Molecular Biology
- Genomics
- Bioinformatics
Background:
- RNA molecules can exhibit dual functionality, acting as both protein-coding and noncoding elements.
- These coding and noncoding RNAs (cncRNAs) are increasingly recognized, yet a centralized repository is lacking.
- Existing research highlights translated ncRNAs and untranslated mRNAs as key examples of cncRNAs.
Purpose of the Study:
- To establish a comprehensive, manually curated database for coding and noncoding RNAs (cncRNAs).
- To provide researchers with a resource for efficient browsing, manipulation, and analysis of experimentally validated cncRNAs.
- To facilitate further investigation into the functions and mechanisms of dual-function RNAs.
Main Methods:
- Manual curation of experimentally supported cncRNA data.
- Development of a dedicated database, cncRNAdb, for organizing and storing information on cncRNAs.
- Inclusion of data across multiple species to ensure broad applicability.
Main Results:
- The cncRNAdb database currently contains approximately 2600 manually curated entries.
- The database covers over 2000 unique RNA molecules, including over 1300 translated ncRNAs and over 600 untranslated mRNAs.
- Entries are supported by experimental evidence detailing cncRNA functions.
Conclusions:
- cncRNAdb serves as a valuable resource for the study of dual-function RNAs.
- The database is expected to aid in elucidating cncRNA functions and mechanisms.
- cncRNAdb may support the development of novel computational methods for predicting cncRNAs.
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