Publication | Open Access
miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions
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2017
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EngineeringGeneticsSpecific MtisTranscriptional RegulationCell DevelopmentLong Non-coding RnaTranscriptomicsMolecular DiagnosticsRna BiologyMirtarbase Update 2018Gene ExpressionEpigenetic RegulationFunctional GenomicsMirna-target InteractionsCell BiologyBioinformaticsMicrorna DetectionComputational BiologySmall RnaSystems BiologyMedicineMirtarbase ServesNon-coding Rna
MicroRNAs are ~22‑nt non‑coding RNAs that negatively regulate mRNA post‑transcriptionally, and miRTarBase was previously developed to catalogue experimentally validated miRNA‑target interactions. The study updates miRTarBase with 422,517 curated miRNA‑target interactions from 4,076 miRNAs and 23,054 target genes sourced from over 8,500 articles. The updated database enables download of reporter‑assay validated target sites, provides target‑site sequences for feature extraction in machine‑learning analyses of miRNA‑target prediction tools, and offers improved browsing options for specific MTIs. Since the 2016 update, strongly supported MTIs have risen by about 1.4‑fold, making miRTarBase a more comprehensively annotated resource for experimentally validated miRNA‑target interactions. miRTarBase is available at http://miRTarBase.mbc.nctu.edu.tw/.
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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