The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions
Open accessAbstract
MicroRNAs (miRNAs) are small non-coding RNAs of ∼ 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles. The number of MTIs curated by strong evidence has increased ∼1.4-fold since the last update in 2016. In this updated version, target sites validated by reporter assay that are available in the literature can be downloaded. The target site sequence can extract new features for analysis via a machine learning approach which can help to evaluate the performance of miRNA-target prediction tools. Furthermore, different ways of browsing enhance user browsing specific MTIs. With these improvements, miRTarBase serves as more comprehensively annotated, experimentally validated miRNA-target interactions databases in the field of miRNA related research. miRTarBase is available at http://miRTarBase.mbc.nctu.edu.tw/.
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Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890
Bartel (2004) · doi:10.1016/s0092-8674(04)00045-5 · Cited by 34,714
O'Leary, N. A., Wright, M. W., Brister, J. R., Ciufo, S., Haddad, D., McVeigh, R., Rajput, B., Robbertse, B., Smith-White, B., Ako-Adjei, D., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1189 · Cited by 6,357
miRBase: annotating high confidence microRNAs using deep sequencing data
Kozomara, A., & Griffiths-Jones, S. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1181 · Cited by 5,073
MicroRNA therapeutics: towards a new era for the management of cancer and other diseases
Rupaimoole, R., & Slack, F. J. (2017) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2016.246 · Cited by 4,741
Integrated genomic characterization of pancreatic ductal adenocarcinoma
Raphael, B. J., Hruban, R. H., Aguirre, A. J., Moffitt, R. A., Yeh, J. J., Stewart, C., Robertson, A. G., Cherniack, A. D., Gupta, M., Getz, G., et al. (2017) · Cancer Cell · doi:10.1016/j.ccell.2017.07.007 · Cited by 2,019
Self-citationSuper-Enhancer-Mediated RNA Processing Revealed by Integrative MicroRNA Network Analysis
Suzuki, H. I., Young, R. A., & Sharp, P. A. (2017) · Cell · doi:10.1016/j.cell.2017.02.015 · Cited by 284
Genome-wide, integrative analysis implicates microRNA dysregulation in autism spectrum disorder
Wu, Y. E., Parikshak, N. N., Belgard, T. G., & Geschwind, D. H. (2016) · Nature Neuroscience · doi:10.1038/nn.4373 · Cited by 195
Self-citationLuna, J. M., Barajas, J. M., Teng, K.-Y., Sun, H.-L., Moore, M. J., Rice, C. M., Darnell, R. B., & Ghoshal, K. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.06.025 · Cited by 80
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Overview of MicroRNA Biogenesis, Mechanisms of Actions, and Circulation
O'Brien, J., Hayder, H., Zayed, Y., & Peng, C. (2018) · Frontiers in Endocrinology · doi:10.3389/fendo.2018.00402 · Cited by 5,287
Raudvere, U., Kolberg, L., Kuzmin, I., Arak, T., Adler, P., Peterson, H., & Vilo, J. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz369 · Cited by 5,045
miRBase: from microRNA sequences to function
Kozomara, A., Birgaoanu, M., & Griffiths-Jones, S. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1141 · Cited by 4,843
An overview of microRNAs: Biology, functions, therapeutics, and analysis methods
Saliminejad, K., Khorram Khorshid, H. R., Soleymani Fard, S., & Ghaffari, S. H. (2019) · Journal of Cellular Physiology · doi:10.1002/jcp.27486 · Cited by 1,872
miRWalk: An online resource for prediction of microRNA binding sites
Sticht, C., De La Torre, C., Parveen, A., & Gretz, N. (2018) · PLOS ONE · doi:10.1371/journal.pone.0206239 · Cited by 1,607
Metadata
- Authors
- Chou, C.-H., Shrestha, S., Yang, C.-D., Chang, N.-W., Lin, Y.-L., Liao, K.-W., Huang, W.-C., Sun, T.-H., Tu, S.-J., Lee, W.-H., Chiew, M.-Y., Tai, C.-S., Wei, T.-Y., Tsai, T.-R., Huang, H.-T., Wang, C.-Y., Wu, H.-Y., Ho, S.-Y., Chen, P.-R., Chuang, C.-H., Hsieh, P.-J., Wu, Y.-S., Chen, W.-L., Li, M.-J., Wu, Y.-C., Huang, X.-Y., Ng, F. L., Buddhakosai, W., Huang, P.-C., Lan, K.-C., Huang, C.-Y., Weng, S.-L., Cheng, Y.-N., Liang, C., Hsu, W.-L., & Huang, H.-D.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-11-06
- Volume
- 46
- Issue
- D1
- Pages
- D296-D302
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2767546566
- Cited by
- 1,811
- References
- 9
- FWCI
- 78.84
- Type
- journal article
- Language
- en
- Open access
- gold
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- Chou, C.-H., Shrestha, S., Yang, C.-D., Chang, N.-W., Lin, Y.-L., Liao, K.-W., Huang, W.-C., Sun, T.-H., Tu, S.-J., Lee, W.-H., Chiew, M.-Y., Tai, C.-S., Wei, T.-Y., Tsai, T.-R., Huang, H.-T., Wang, C.-Y., Wu, H.-Y., Ho, S.-Y., Chen, P.-R., . . . Huang, H.-D. (2018). miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions. Nucleic Acids Research. https://doi.org/10.1093/nar/gkx1067
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