ArticleBMC bioinformatics2015
ComiRNet: a web-based system for the analysis of miRNA-gene regulatory networks.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed, 45 citations in OpenAlex.
- miRNA-Targeted Vaccines: A Promising Approach for Viral Attenuation and Immunogenicity Enhancement.Current gene therapy · 2025Review
- Bioinformatics Prediction for Network-Based Integrative Multi-Omics Expression Data Analysis in Hirschsprung Disease.Biomolecules · 2024Article
- MicroRNA Databases and Tools.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Multi-task learning for the simultaneous reconstruction of the human and mouse gene regulatory networks.Scientific reports · 2020Article
- Prediction of new associations between ncRNAs and diseases exploiting multi-type hierarchical clustering.BMC bioinformatics · 2020Article
- miR-106a-5p Functions as a Tumor Suppressor by Targeting VEGFA in Renal Cell Carcinoma.Disease markers · 2020Article
- In silico prediction of potential miRNA-disease association using an integrative bioinformatics approach based on kernel fusion.Journal of cellular and molecular medicine · 2020Article
- Network Diffusion Approach to Predict LncRNA Disease Associations Using Multi-Type Biological Networks: LION.Frontiers in physiology · 2019Article
- Article
- Combinatorial ensemble miRNA target prediction of co-regulation networks with non-prediction data.Nucleic acids research · 2017Article
- miRNAs target databases: developmental methods and target identification techniques with functional annotations.Cellular and molecular life sciences : CMLS · 2017Review
- Preface: BITS2014, the annual meeting of the Italian Society of Bioinformatics.BMC bioinformatics · 2015Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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 regulatory networks (MGRNs).
conclusionsComiRNet represents a valuable resource for elucidating the miRNAs' role in complex biological processes by exploiting data on their putative function in the context of MGRNs. ComiRnet currently stores about 5 million predicted MTIs between 934 human miRNAs and 30,875 mRNAs, as well as 15 bicluster hierarchies, each of which represents MGRNs at different levels of granularity. The database can be freely accessed at: http://comirnet.di.uniba.it.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.