is a machine learning algorithm based on SVM (support vector machine)
that serves as a post-processing filter for the miRNA:target duplexes predicted by softwares such
For an input duplex, MiRTif outputs an SVM score indicating whether the
input is likely to be a positive interaction.
The SVM is trained with validated positive and negative miRNA:target
interactions, obtained from TarBase
These interactions possess the well-accepted miRNA:target binding properties such as strong seed complementarity
and high binding energy, and are believed to be authentic. Therefore, MiRTif is only applicable to interactions
obtained from other prediction software.
Users have two options to predict a miRNA:target interaction. You can input duplexes one at a time
or upload a text file containing the list of the duplexes.
It takes a few seconds to process a duplex in general. Nevertheless querying a long list of duplexes may require
some time, the results can be emailed to you when finished.
manuscript in preparation
Selected informative features
MicroRNAs in the training set
For any comments please contact:
Dr. Kuo-Bin Li
Center for Systems and Synthetic Biology
National Yang-Ming University, Taipei, Taiwan