Welcome to miR-Synth!

RNAi is a powerful tool for the regulation of gene expression. It is widely and successfully employed in functional studies and is now emerging as a promising therapeutic approach. Several RNAi-based clinical trials suggest encouraging results in the treatment of a variety of diseases, including cancer.

miR-Synth is a computational resource for the design of synthetic miRNAs (a-miR) able to target multiple genes in multiple sites. It combines well-established knowledge on miRNA targeting together with siRNA design rules and empirical observations on validated miRNA/target interactions into a pipeline which allows the rational design of artificial miRNAs.

The designed a-miRs are evaluated by a scoring function based on six different features of validated miRNA/target interactions: seed type, pairing of the a-miR 3' region, AU content of the binding site and its surrounding regions, a-miR nucleotide composition, structural accessibility of the binding site, presence of ARE and CPE motifs upstream of the binding sites. For any given a-miR, each feature is assigned a score ranging from 0 to 1 and a total repression score is calculated by combining the tree-based multiple linear regression learning system M5P with conditional inference trees (CTree). In particular, a-miRs are first ranked according to the CTree score, which assigns them to one of four different classes, and subsequently by M5P score.

Choose "Design a-miR" to start designing artificial miRNAs for your targets.


Alessandro Laganà, Mario Acunzo, Giulia Romano, Alfredo Pulvirenti, Dario Veneziano, Luciano Cascione, Rosalba Giugno, Pierluigi Gasparini, Dennis Shasha, Alfredo Ferro and Carlo M. Croce
miR-Synth: a computational resource for the design of multi-site multi-target synthetic miRNAs
Nucleic Acids Research (2014); doi: 10.1093/nar/gku202