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[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]
ComiR is a web tool for combinatorial microRNA (miRNA) target prediction. Given an messenger RNA (mRNA) in human, mouse, fly or worm genomes, ComiR predicts whether a given mRNA is targeted by a set of miRNAs.
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 ...
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 ...
Sfold is a software program developed to predict probable RNA secondary structures through structure ensemble sampling and centroid predictions [1] [2] with a focus on assessment of RNA target accessibility, [3] for major applications to the rational design of siRNAs [4] in the suppression of gene expressions, and to the identification of targets for regulatory RNAs particularly microRNAs.
Cupid is a 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.
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.
It is used especially when the read length of the sequencing machine is longer than the sequenced molecule, like the microRNA case. Deconseq Detect and remove contaminations from sequence data. Erne-Filter [ 26 ] is a short string alignment package whose goal is to provide an all-inclusive set of tools to handle short (NGS-like) reads.
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