Now showing items 1-4 of 4
Machine learning methods for microRNA gene prediction
(Humana Press, 2014)
MicroRNAs (miRNAs) are single-stranded, small, noncoding RNAs of about 22 nucleotides in length, which control gene expression at the posttranscriptional level through translational inhibition, degradation, adenylation, ...
Feature selection for microRNA target prediction comparison of one-class feature selection methodologies
Traditionally, machine learning algorithms build classification models from positive and negative examples. Recently, one-class classification (OCC) receives increasing attention in machine learning for problems where the ...
The impact of feature selection on one and two-class classification performance for plant microRNAs
(PeerJ Inc., 2016)
MicroRNAs (miRNAs) are short nucleotide sequences that form a typical hairpin structure which is recognized by a complex enzyme machinery. It ultimately leads to the incorporation of 18-24 nt long mature miRNAs into RISC ...
Feature selection has a large impact on one-class classification accuracy for micrornas in plants
(Hindawi Publishing Corporation, 2016)
MicroRNAs (miRNAs) are short RNA sequences involved in posttranscriptional gene regulation. Their experimental analysis is complicated and, therefore, needs to be supplemented with computational miRNA detection. Currently ...