miRNet

Input Type

Click on a module below to start

Mixed input types

Multiple query types

Upload a data table

Expression table

RT-qPCR data

Select from a database

Diseases

Small compounds

Epigenetic modifiers

Xeno-miR explorer

Upload a query list

miRNAs

SNPs

Genes

ncRNAs

Transcription factors

Xeno-miRs

News & Updates

Please reach us via our OmicsForum to ask questions related to miRNet.
Added the FDR column to the download table of enrichment analysis result (08/02/2022);
Upgraded R to version 4.1.3 and code refactoring (05/13/2022);
For miRNetR users, the path to sqlite database is: https://www.xialab.ca/resources/sqlite/mir2gene.sqlite (02/24/2022);
Upgraded to PrimeFaces 11 (12/20/2021);
Added topology distribution measures for Network Topology filter (07/04/2021);

Key Features

Support for various inputs & statistics: miRNet accepts a list of miRNAs, miR-SNPs, genes, transcription factors, small molecules, ncRNAs, diseases, epigenetic modifers, any of their combinations or a data table from microarray, RNAseq or RT-qPCR experiments. miRNet supports differential analysis using limma, edgeR and HTqPCR methods; enrichment analysis using standard hypergeometric tests and unbiased random sampling.
Comprehensive functional annotation: miRNet integrates data from 14 different miRNA databases - TarBase, miRTarBase, miRecords, miRanda (S mansoni only), miR2Disease, HMDD, PhenomiR, SM2miR, PharmacomiR, EpimiR, starBase, TransmiR, ADmiRE, and TAM 2.0. It currently supports Human, Mouse, Rat, Cattle, Pig, Chicken, Zebra fish, Fruit fly, C. elegans, and S. mansoni.
Exploring xeno-miRNAs and their potential targets: miRNet currently supports six hosts (Human, Mouse, Chicken, Fruit fly, and C. elegans) with xeno-miRNAs reported from over 50 species. It contains over 400 experimentally detected xeno-miRNAs supplemented with 1000 computational predicted transportable miRNAs. Their potential gene targets are predicted using two algorithms - miRanda and TarPmiR.
Creation of miRNA-target interaction networks: miRNet provides a wide array of options to allow researchers to build miRNA-target interaction networks at different confidence levels. The resulting network can be further optimized using different algorithms to improve visualization and understanding. The network algorithm includes Force Atlas, Fruchterman-Reingold, Graphopt, Large Graph, Random, Reduce Overlap, Bipartite/Tripartite, Concentric Circle, and Backbone algorithm.
High-performance network visual analytics: miRNet allows users to easily create miRNA-centric networks consisting of different molecules or phenotypes of interest: genes, diseases, small molecules, SNPs (affecting miRNAs or their binding sites), ncRNAs (lncRNA, sncRNA, circRNA or peudogene), epigenetic modifiers, and transcription factors. The system supports zooming, batch highlighting, point-and-click, drag-and-drop, enrichment analysis, etc. to enable users to intuitively explore miRNAs, targets and functions.

Publications

Chang, L., Zhou, G., Soufan, O. and Xia, J. (2020) miRNet 2.0 - network-based visual analytics for miRNA functional analysis and systems biology. Nucl. Acids Res. (doi: 10.1093/nar/gkaa467)
Fan, Y., Habib, M. and Xia, J. (2018) Xeno-miRNet: a comprehensive database and analytics platform to explore xeno-miRNAs and their potential targets PeerJ 6:e5650
Fan Y. and Xia, J. (2018) miRNet: functional analysis and visual exploration of miRNA-target interactions in a network context Computational Cell Biology. Humana Press, New York, NY
Fan Y, Siklenka, K., Arora, SK., Ribeiro, P., Kimmins, S. and Xia, J. (2016) miRNet - dissecting miRNA-target interactions and functional associations through network-based visual analysis. Nucl. Acids Res. 44 W135–141

Acknowledgements

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