The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
miRTarBase update 2022: an informative resource for experimentally validated miRNA–target interactions
Open accessAbstract
MicroRNAs (miRNAs) are noncoding RNAs with 18–26 nucleotides; they pair with target mRNAs to regulate gene expression and produce significant changes in various physiological and pathological processes. In recent years, the interaction between miRNAs and their target genes has become one of the mainstream directions for drug development. As a large-scale biological database that mainly provides miRNA–target interactions (MTIs) verified by biological experiments, miRTarBase has undergone five revisions and enhancements. The database has accumulated >2 200 449 verified MTIs from 13 389 manually curated articles and CLIP-seq data. An optimized scoring system is adopted to enhance this update’s critical recognition of MTI-related articles and corresponding disease information. In addition, single-nucleotide polymorphisms and disease-related variants related to the binding efficiency of miRNA and target were characterized in miRNAs and gene 3′ untranslated regions. miRNA expression profiles across extracellular vesicles, blood and different tissues, including exosomal miRNAs and tissue-specific miRNAs, were integrated to explore miRNA functions and biomarkers. For the user interface, we have classified attributes, including RNA expression, specific interaction, protein expression and biological function, for various validation experiments related to the role of miRNA. We also used seed sequence information to evaluate the binding sites of miRNA. In summary, these enhancements render miRTarBase as one of the most research-amicable MTI databases that contain comprehensive and experimentally verified annotations. The newly updated version of miRTarBase is now available at https://miRTarBase.cuhk.edu.cn/.
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Kolberg, L., Raudvere, U., Kuzmin, I., Adler, P., Vilo, J., & Peterson, H. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad347 · Cited by 1,673
The miRNA–target interactions: An underestimated intricacy
Diener, C., Keller, A., & Meese, E. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkad1142 · Cited by 248
An ontology-based knowledge graph for representing interactions involving RNA molecules
Cavalleri, E., Cabri, A., Soto-Gomez, M., Bonfitto, S., Perlasca, P., Gliozzo, J., Callahan, T. J., Reese, J., Robinson, P. N., Casiraghi, E., et al. (2024) · Scientific Data · doi:10.1038/s41597-024-03673-7 · Cited by 33
Lai, X., Zhang, Y., Li, M., Yu, S., Wang, S., Zhang, S., Niu, H., Chen, L., Lan, X., Zhang, J., et al. (2025) · Molecular Carcinogenesis · doi:10.1002/mc.23878 · Cited by 11
Rudhra, O., & Singh, S. K. (2026) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2026.111822 · Cited by 1
Metadata
- Authors
- Huang, H.-Y., Lin, Y.-C.-D., Cui, S., Huang, Y., Tang, Y., Xu, J., Bao, J., Li, Y., Wen, J., Zuo, H., Wang, W., Li, J., Ni, J., Ruan, Y., Li, L., Chen, Y., Xie, Y., Zhu, Z., Cai, X., Chen, X., Yao, L., Chen, Y., Luo, Y., LuXu, S., Luo, M., Chiu, C.-M., Ma, K., Zhu, L., Cheng, G.-J., Bai, C., Chiang, Y.-C., Wang, L., Wei, F., Lee, T.-Y., & Huang, H.-D.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2021-11-30
- Volume
- 50
- Issue
- D1
- Pages
- D222-D230
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W4200043367
- Cited by
- 983
- References
- 61
- FWCI
- 51.72
- Type
- journal article
- Language
- en
- Open access
- gold
- Funders
- National Natural Science Foundation of China (32070674, 32070659)
- Key Program of Guangdong Basic and Applied Basic Research Fund (2020B1515120069)
- Shenzhen City and Longgang District for the Warshel Institute for Computational Biology
- Ganghong Young Scholar Development Fund (2021E0005, 2021E007)
- Science, Technology and Innovation Commission of Shenzhen Municipality (JCYJ20200109150003938)
- Guangdong Province Basic and Applied Basic Research Fund (2021A1515012447)
- Basic research project of Shenzhen Science and Technology Research Projects (JCYJ20190808102405474)
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- Huang, H.-Y., Lin, Y.-C.-D., Cui, S., Huang, Y., Tang, Y., Xu, J., Bao, J., Li, Y., Wen, J., Zuo, H., Wang, W., Li, J., Ni, J., Ruan, Y., Li, L., Chen, Y., Xie, Y., Zhu, Z., Cai, X., . . . Huang, H.-D. (2022). miRTarBase update 2022: an informative resource for experimentally validated miRNA–target interactions. Nucleic Acids Research. https://doi.org/10.1093/nar/gkab1079
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
