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miRTarBase 2020: updates to the experimentally validated microRNA-target interaction database
Hsi-Yuan Huang1,2, Yang-Chi-Dung Lin1,2, Jing Li1,2
1School of Life and Health Sciences, The Chinese University of Hong Kong, Shenzhen, Longgang District, Shenzhen, Guangdong Province 518172, China.
The miRTarBase database now offers enhanced information on microRNA-target interactions (MTIs) using text mining and integrated biological databases. This update significantly expands experimentally validated MTIs, including high-throughput evidence, for comprehensive regulatory network analysis.
Area of Science:
- Molecular Biology
- Bioinformatics
- Genomics
Background:
- MicroRNAs (miRNAs) are small non-coding RNAs regulating gene expression post-transcriptionally.
- miRTarBase curates experimentally validated miRNA-target interactions (MTIs).
- The database previously contained over 13,404 validated MTIs from manual curation.
Purpose of the Study:
- To enhance miRTarBase with improved MTI recognition and expanded data integration.
- To provide a more comprehensive resource for studying miRNA regulatory networks.
- To incorporate high-throughput experimental validation data for MTIs.
Main Methods:
- Incorporation of a text-mining system with a scoring mechanism for MTI article identification.
- Integration of diverse biological databases for miRNA regulatory network and expression data.
- Inclusion of MTIs validated by high-throughput technologies like CLIP-seq.
Main Results:
- Enhanced identification of MTI-related literature.
- Expanded dataset including miRNA regulators and expression profiles in blood.
- Significant increase in MTIs supported by high-throughput experimental evidence.
- miRTarBase now provides a more comprehensive view of miRNA regulatory mechanisms.
Conclusions:
- The updated miRTarBase is a leading resource for experimentally validated miRNA-target interactions.
- Improvements facilitate deeper investigation of miRNA upstream and downstream regulations.
- The database is a valuable tool for researchers in molecular biology and genomics.
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