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Provides for the first time hundreds of thousands of high quality manually curated experimentally validated miRNA:gene interactions, enhanced with detailed meta-data. With DIANA-TarBase v7.0 you can easily identify positive or negative experimental results, the utilized experimental methodology, experimental conditions including cell/tissue type and treatment. The new interface provides also advanced information ranging from the binding site location, as identified experimentally as well as in silico, to the primer sequences used for cloning experiments.


Identifies canonical and non-canonical miRNA-binding sites based on de novo motif identification from Ago2 peaks and prediction of miRNA::RNA heteroduplexes. miRBShunter extracts peak sequences, annotates on the genome and converts miRNA sequences in Homer format by using Homer software. This pipeline works for mouse and human miRNA-mRNA pairs. miRBShunter is a valuable resource for researchers working on miRNA biology due to its easy applicability and reliability of the results.


A model for miRNA target prediction through discriminative learning on transcriptome-wide AGO CLIP and CLASH profiles. Our goal was to learn to accurately predict biochemical miRNA-target site interactions, rather than the extent of regulation, in order to increase the sensitivity of miRNA target prediction and learn physiological targeting rules. chimiRic produces more accurate predictions than state-of-the-art methods based on indirect measurements. Moreover, interpretation of the learned model reveals novel features of miRNA-mRNA interactions, including potential cooperativity with specific RNA-binding proteins.