miRNet

-- a miRNA-centric network visual analytics platform

Input types:

	Upload a query list
	Select from database
	Upload a data table
	Mixed input types

News & Updates

Added support for edge bundling to reduce edge crossing in large networks (03/28/2020);
Added support for p-value adjustment in Function Explorer (03/28/2020);
Users can easily update colors and sizes for different node types using Global Node Styles pane (03/19/2020);
Updated FAQs and the miRNet Overview tutorial (03/13/2020);
Added the "Module Explorer" panel for better network visual analytics (03/08/2020);
Fixed performance issue of several algorithms for large network layout (03/02/2020);
Added two layout algorithms (Concentric and Backbone) for multipartite networks (02/24/2020);
Code cleaning and refactoring (02/14/2020);
Added support for the latest miRBase ID (v22) (02/09/2020);
Added six miRNA set libraries (Function, Disease, Transcription Factor, Cluster, Family, Tissue specificity) for enrichment analysis (02/09/2020);
Added support for computing minimum subnetworks based on queries (02/01/2020);
Added support for highlighting seed nodes (01/31/2020);
Optimized workflow (01/28/2020);
Code cleaning and refactoring (01/24/2020);
Fixed issue with data filtering in the Network Tools (01/23/2020);
Updated tutorials and FAQs (01/02/2020);
Enhanced network visualization & customization. Users can now customize background color, node shape & label, edge color & opacity (01/02/2020);

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.