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Publication Information

PubMed ID
Public Release Type
Journal
Publication Year
2023
Affiliation
1 Department of Physiological Nursing, University of California, San Francisco, San Francisco, CA, 94143, USA 2 Bluestone Center for Clinical Research, New York University, New York, CA, 10010, USA 3 Department of Oral and Maxillofacial Surgery, New York University, New York, CA, 10010, USA 4 Center for Genomic Medicine and Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Boston, CA, 02114, USA 5 Programs in Metabolism and Medical & Population Genetics, Broad Institute, Cambridge, MA, 02142, USA 6 Department of Medicine, Harvard Medical School, Boston, MA, Postcode, USA 7 Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, 94143, USA
Authors
Aouizerat BE, Asam K, Florez JC, Flowers E, Kariuki D, Lewis KA
Studies

Abstract

MicroRNAs (miRs) may contribute to disease etiology by influencing gene expression. Numerous databases are available for miR target prediction and validation, but their functionality is varied, and outputs are not standardized. The purpose of this review is to identify and describe databases for cataloguing validated miR targets. Using Tools4miRs and PubMed, we identified databases with experimentally validated targets, human data, and a focus on miR-mRNA interactions. Data were extracted about the number of times each database was cited, number of miRs, target genes, and interactions per database, experimental methodology, and key features of each database. The search yielded ten databases, which in order of most cited to least were: miRTarBase, starBase/ENCORI, DIANA-TarBase, miRWalk, miRecords, miRGator, miRSystem, miRGate, miRSel and targetHub. Findings from this review suggest that the information presented within miR target validation databases can be enhanced by adding features such as flexibility in performing queries in multiple ways, downloadable data, ongoing updates, and integrating tools for further MTI analysis. This review is designed to aid researchers, especially those new to miR bioinformatics tools, in database selection and to offer considerations for future development and upkeep of validation tools.