RepTar: a database of predicted cellular targets of host and viral miRNAs

Computational identification of putative microRNA (miRNA) targets is an important step towards elucidating miRNA functions. Several miRNA target-prediction algorithms have been developed followed by publicly available databases of these predictions. Here we present a new database offering miRNA target predictions of several binding types, identified by our recently developed modular algorithm RepTar. RepTar is based on identification of repetitive elements in 30 -UTRs and is independent of both evolutionary conservation and conventional binding patterns (i.e. Watson–Crick pairing of ‘seed’ regions). The modularity of RepTar enables the prediction of targets with conventional seed sites as well as rarer targets with non-conventional sites, such as sites with seed wobbles (G-U pairing in the seed region), 30 -compensatory sites and the newly discovered centered sites. Furthermore, RepTar’s independence of conservation enables the prediction of cellular targets of the less evolut...

• Type: Journal
• Year: 2011
• Where: NAR
• Authors: Naama Elefant, Amnon Berger, Harel Shein, Matan Hofree, Hanah Margalit, Yael Altuvia
• Keywords: Cellular Targets, NAR 2011, Prediction Algorithms, Repetitive Elements