In particular, supervised machine learning has been used to great effect in numerous bioinformatics prediction methods.
The main drawback of computational methods is the largely unknown accuracy of their predictions a drawback that is exacerbated by the lack of an established framework for validating the accuracy of the numerous computational prediction methods that populate the literature.
Therefore, numerous miRNA target prediction methods have been proposed such as miRanda [ 22], TargetScan(S) [ 23], RNA22 [ 24], Diana-MicroT [ 25], PicTar [ 26], RNAhybrid [ 27], and miTarget [ 28], based on seed complementarity, thermodynamics, conservation, Bayesian statistics, SVM, HMM, artificial neural networks, etc.
It acts as a meta-database which maps all interaction evidence onto a common set of genomes and proteins by integrating information from numerous sources, including experimental repositories, computational prediction methods and public text collections.
It weights and integrates information from numerous sources, including experimental repositories, computational prediction methods and public text collections.
STRING includes both physical and functional interactions integrated from numerous sources, including experimental repositories, computational prediction methods and public text collections; uses a scoring system to weigh the evidence of each interaction; and includes the interactions between 14532 proteins (Entrez gene ID) of human genome.
These interactions contain direct (physical) and indirect (functional) interactions, derived from numerous sources such as experimental repositories, computational prediction methods.
Previous studies discovered thousands of miRNAs and numerous miRNA target genes mainly through computation and prediction methods which produced high rates of false positive prediction.
The experimental databank, from numerous independent research studies, is then utilized to develop the new prediction methods to evaluate local heat transfer coefficients and pressure drops.
