News & Updates
  • Added a new module to support miRNA and transcription factor interactions (12/03/2019);
  • Updated miRNA-disease interaction data based on new release of HMDD v3.2 (11/08/2019);
  • Updated R from 3.5.1 to the latest version (3.6.1) (10/16/2019);
  • Added support for pig (429 miRNAs and 8353 target genes) (10/09/2019);
  • Minor code refactoring for better performance (06/06/2019);
  • Upgraded the web framework to PrimeFaces 7.0 (05/29/2019);
  • Fixed the issue with file uploading (03/11/2019);
  • Fixed the bugs in tissue mapping (03/07/2019);
  • Added two modules to support analysis of xeno-miRNAs (xenomiRs) and their potential targets in different hosts (02/25/2019);
  • Updated the interface for improved performance and better user experience (02/20/2019);
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Key Features
  • Support for various inputs & statistics: miRNet accepts a list of miRNAs or targets, 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 twelve different miRNA databases - TarBase, miRTarBase, miRecords, miRanda (S mansoni only), miR2Disease, HMDD, PhenomiR, SM2miR, PharmacomiR, EpimiR, starBase, and TransmiR. 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.
  • High-performance network visual analytics: miRNet offers six types of networks on miRNA-gene, miRNA-disease, miRNA-small molecule, miRNA-lncRNA, miRNA-epigenetic modifier, and miRNA-transcription factor. The system supports zooming, highlighting, point-and-click, drag-and-drop, enrichment analysis, etc. to enable users to intuitively explore miRNAs, targets and functions.
Publications
Acknowledgements
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