TY - JOUR AU - D'Elia, Domenica AB - Background: The understanding of mechanisms and functions of microRNAs (miRNAs) is fundamental for the study of many biological processes and for the elucidation of the pathogenesis of many human diseases. Technological advances represented by high-throughput technologies, such as microarray and next-generation sequencing, have significantly aided miRNA research in the last decade. Nevertheless, the identification of true miRNA targets and the complete elucidation of the rules governing their functional targeting remain nebulous. Computational tools have been proven to be fundamental for guiding experimental validations for the discovery of new miRNAs, for the identification of their targets and for the elucidation of their regulatory mechanisms. Description: ComiRNet (Co-clustered miRNA Regulatory Networks) is a web-based database specifically designed to provide biologists and clinicians with user-friendly and effective tools for the study of miRNA-gene target interaction data and for the discovery of miRNA functions and mechanisms. Data in ComiRNet are produced by a combined computational approach based on: 1) a semi-supervised ensemble-based classifier, which learns to combine miRNA-gene target interactions (MTIs) from several prediction algorithms, and 2) the biclustering algorithm HOCCLUS2, which exploits the large set of produced predictions, with the associated probabilities, to identify overlapping and hierarchically organized biclusters that represent miRNA-gene TI - ComiRNet: a web-based system for the analysis of miRNA-gene regulatory networks JF - BMC Bioinformatics DO - 10.1186/1471-2105-16-S9-S7 DA - 2015-06-01 UR - https://www.deepdyve.com/lp/springer-journals/comirnet-a-web-based-system-for-the-analysis-of-mirna-gene-regulatory-S23Ku2vgfq SP - 1 EP - 18 VL - 16 IS - 9 DP - DeepDyve ER -