miRNet
- a miRNA-centric network visual analytics platform
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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
Fixed the issue with network export (
01/29/2021
);
Fixed the issue with tissue mapping in gene, TF and ncRNA modules (
01/28/2021
);
Fixed the issue with empirical sampling when microservice failed (
12/22/2020
);
Fixed the issue with Steiner Forest algorithm (
11/24/2020
);
Check out our
video tutorials
for intuitive network visual analytics (
10/15/2020
);
Updated R from 3.6.2 to 4.0.2 and code refactoring (
09/15/2020
);
Added support for gradient background (
09/14/2020
);
Added support to show
piechart nodes
with multiple annotations (i.e. lncRNA and Gene, TF and Gene) (
07/30/2020
);
Users can now select the original database for miRNA gene target analysis (
07/06/2020
);
Our
miRNet 2.0 paper
is now accepted by NAR 2020 web server issue (
05/21/2020
);
Added support for the
Human Reference Interactome (HuRI)
map (
05/14/2020
);
Added detailed online tutorials (
04/24/2020
)
Read more ......
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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