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The experimentally validated microRNA-target interactions database. As a database, miRTarBase has accumulated more than three hundred and sixty thousand miRNA-target interactions (MTIs), which are collected by manually surveying pertinent literature after NLP of the text systematically to filter research articles related to functional studies ...
[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.
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
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 ...
The human genome may encode over 1900 miRNAs, [8] [9] However, only about 500 human miRNAs represent bona fide miRNAs in the manually curated miRNA gene database MirGeneDB. [10] miRNAs are abundant in many mammalian cell types. [11] [12] They appear to target about 60% of the genes of humans and other mammals.
Program to recognize vertebrate RNA polymerase II promoters: Vertebrates [7] EasyGene: The gene finder is based on a hidden Markov model (HMM) that is automatically estimated for a new genome. Prokaryotes [8] [9] EuGene: Integrative gene finding: Prokaryotes, Eukaryotes [10] [11] FGENESH: HMM-based gene structure prediction: multiple genes ...
Prediction of transmembrane helices to identify transmembrane proteins. [111] 2001 TMPred: The TMpred program makes a prediction of membrane-spanning regions and their orientation. The algorithm is based on the statistical analysis of TMbase, a database of naturally occurring transmembrane proteins (bio.tools entry) [112]