Publications

• Chang, L. and Xia, J. (2022) MicroRNA Regulatory Network Analysis Using miRNet 2.0 Transcription Factor Regulatory Networks, 185-204. Humana Press, New York, NY
• 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

News & Updates

• For miRNetR users, the path to the sqlite database is: https://www.xialab.ca/resources/sqlite/mir2gene.sqlite;
• Minor text updates and interface improvements (08/18/2023)
• Removed support for searching predicted xeno-miRs based on the retraction notice for the original paper (05/13/2023);
• Upgraded R to version 4.2.2 (01/13/2023);

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.

Acknowledgements