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PITA, incorporates the role of target-site accessibility, as determined by base-pairing interactions within the mRNA, in microRNA target recognition. webserver, predictions: predictions [16] RepTar: A database of inverse miRNA target predictions, based on the RepTar algorithm that is independent of evolutionary conservation considerations and ...
[10] which provide predictions for mammals, zebrafish, insects, and nematodes centered on the genes of human, mouse, zebrafish, Drosophila melanogaster, and Caenorhabditis elegans, respectively. Compared to other target-prediction tools [which?] TargetScan provides accurate rankings of the predicted targets for each miRNA. [6]
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.
Method for simultaneous prediction of miRNA-target interactions and their mediated competing endogenous RNA (ceRNA) interactions. It is an integrative approach significantly improves on miRNA-target prediction accuracy as assessed by both mRNA and protein level measurements in breast cancer cell lines.
SwissTargetPrediction is a web server for target prediction of bioactive small molecules. This website allows you to predict the targets of a small molecule. Using a combination of 2D and 3D similarity measures, it compares the query molecule to a library of 280 000 compounds active on more than 2000 targets of 5 different organisms.
MicroRNA sequencing (miRNA-seq), a type of RNA-Seq, is the use of next-generation sequencing or massively parallel high-throughput DNA sequencing to sequence microRNAs, also called miRNAs. miRNA-seq differs from other forms of RNA-seq in that input material is often enriched for small RNAs. miRNA-seq allows researchers to examine tissue-specific expression patterns, disease associations, and ...
Computationally predicted miRNA targets derived from TargetScan are comparable to CLIP in identifying miRNA targets, raising questions as to its utility relative to existing predictions. [46] Because CLIP methods rely on immunoprecipitation, crosslinked RNA could in some cases affect antibody-epitope interactions.
starBase database: decoding miRNA-mRNA, miRNA-lncRNA, miRNA-sncRNA, miRNA-circRNA, miRNA-pseudogene, protein-lncRNA, protein-ncRNA interactions and ceRNA networks from PAR-CLIP(CLIP-Seq, HITS-CLIP,iCLIP) data, and TargetScan [1], PicTar, RNA22, miRanda and PITA microRNA target sites.
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related to: miranda for mirna target prediction