University of Colorado Cancer Center, A National Cancer Institute-designated Comprehensive Cancer Center

The multiMiR R package and database:
Integration of microRNA-target interactions along with their disease and drug associations
(Nucleic Acids Res. 2014 Jul 24. pii: gku631)


microRNAs (miRNAs) regulate expression by promoting degradation or repressing translation of target transcripts. miRNA target sites have been catalogued in databases based on experimental validation and computational prediction using a variety of algorithms. Several online resources provide collections of multiple databases but need to be imported into other software, such as R, for processing, tabulation, graphing and computation. Currently available miRNA target site packages in R are limited in the number of databases, types of databases and flexibility.

The R package multiMiR, with web server at, is a comprehensive collection of predicted and validated miRNA-target interactions and their associations with diseases and drugs.


multiMiR includes several novel features not available in existing R packages:
  1. Compilation of nearly 50 million records from 14 different databases, more than any other collection
  2. Expansion of databases to those based on disease annotation and drug response, in addition to many experimental and computational databases
  3. User-defined cutoffs for predicted binding strength to provide the most confident selection
  4. Package enables retrieval of miRNA-target interactions from 14 external databases in R without the need to visit all these databases
  5. Advanced users can also submit SQL queries to the web server to retrieve results

Database v2.2 - updated 8/8/2017

CategoryExternal DatabaseVersionLast UpdateHuman RecordsMouse RecordsRat RecordsTotal Records
Validated miRNA-target InteractionsmiRecords4Apr 27, 201324254491713045
miRTarBase6.1Sept, 201544004048731470489281
Predicted miRNA-target InteractionsDIANA-microT-CDS5Sept, 201376646023747171011411773
ElMMo5Jan, 2011395911214491335471915955436
MicroCosm5Sept, 20097629875347353533781651100
miRandaN/AAug, 2010542995523798812473688057204
miRDB5Aug, 201411248316541921951361974159
PicTar2Dec 21, 20124040663022360706302
PITA6Aug 31, 200877109365163153012874089
TargetScan7.1Jun, 20161380162110452055024253676
miRNA-disease/drug AssociationsmiR2DiseaseN/AMar 14, 20112875002875
Pharmaco-miR (Verified Sets)N/AN/A30850313
PhenomiR2Feb 15, 201115138491015629

Previous Database Versions


Download Installation Documentation
The current version of the multiMiR R Package is 0.99.5 and can be downloaded from

Note: The version of the R package and Database have been seperated. The R package has
been set back to 0.99 while the Database will continue from v2.1. The R package will now
allow you to choose pevious database versions if desired to reproduce previous results.
multiMiR requires the XML and RCurl packages from R. The packages can be installed from R by typing:

# To install multiMiR, first install suggested package BiocStyle

# Now install devtools (for installing from GitHub repositories)

# Now install the development version of the multiMiR package
devtools::install_github("kechrislab/multimir", build_vignettes = TRUE)
multiMiR is distributed with a Userís Guide illustrating examples of package functions and queries.

The User's Guide can be downloaded here or viewed from R by typing:

More information about this version and previous versions.

Feature Request/Bug Report:

If there is a feature you would like to suggest, or a bug you would like to report, please submit an issue through GitHub.


multiMiR is developed by Yuanbin Ru at BioMarin Pharmaceutical Inc., Matt Mulvahill, Spencer Mahaffey, & Katerina Kechris at the University of Colorado Denver.


If you use multiMiR, please cite

Yuanbin Ru*, Katerina J. Kechris*, Boris Tabakoff, Paula Hoffman, Richard A. Radcliffe, Russell Bowler, Spencer Mahaffey, Simona Rossi, George A. Calin, Lynne Bemis, and Dan Theodorescu. (2014) The multiMiR R package and database: integration of microRNA-target interactions along with their disease and drug associations. Nucleic Acids Research, doi: 10.1093/nar/gku631. (* Equal contribution)