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Web server which predicts targets for miRNAs and provides functional information on the predicted miRNA:target gene interaction from various online biological resources. Updates enable the association of miRNAs to diseases through bibliographic analysis and connection to the UCSC genome browser. Updates include sophisticated workflows.
an integrated resource for microRNA-target interactions. database: website [14] PicTar: PicTar is Combinatorial microRNA target predictions. database, webserver, predictions: website [15] PITA: PITA, incorporates the role of target-site accessibility, as determined by base-pairing interactions within the mRNA, in microRNA target recognition.
database [4] ceRNAFunction: ceRNAFunction is a web server to predict lncRNA and protein functions from pan-cancer ceRNA networks using 13 functional terms (including: GO, KEGG, BIOCARTA, etc.). webserver [3] [5] Cupid: Cupid is a method for simultaneous prediction of miRNA-target interactions and their mediated competing endogenous RNA (ceRNA ...
In bioinformatics, TargetScan is a web server that predicts biological targets of microRNAs (miRNAs) by searching for the presence of sites that match the seed region of each miRNA. [1] For many species, other types of sites, known as 3'-compensatory sites [ 1 ] are also identified.
Name Description Knots [Note 1]Links References trRosettaRNA: trRosettaRNA is an algorithm for automated prediction of RNA 3D structure. It builds the RNA structure by Rosetta energy minimization, with deep learning restraints from a transformer network (RNAformer). trRosettaRNA has been validated in blind tests, including CASP15 and RNA-Puzzles, which suggests that the automated predictions ...
BIMSB doRiNA database: a database for exploring protein-RNA, microRNA-target interactions from PAR-CLIP,CLIP-Seq, HITS-CLIP,iCLIP data, and PICTAR microRNA target site predictions. miRTarCLIP: A computational approach for identifying microRNA-target interactions using high-throughput CLIP and PAR-CLIP sequencing.
Rna22 is a pattern-based algorithm for the discovery of microRNA target sites and the corresponding heteroduplexes. [1]The algorithm is conceptually distinct from other methods for predicting microRNA:mRNA heteroduplexes in that it does not use experimentally validated heteroduplexes for training, instead relying only on the sequences of known mature miRNAs that are found in the public databases.
StarBase; Content; Description: microRNA-mRNA interaction maps from Argonaute CLIP-Seq and Degradome-Seq data.: Contact; Research center: Sun Yat-sen University: Laboratory: Key Laboratory of Gene Engineering of the Ministry of Education