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Now showing items 11-14 of 14
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 ...
Can MiRBase provide positive data for machine learning for the detection of MiRNA hairpins?
(Informationsmanagement in der Biotechnologie e.V., 2013)
Experimental detection and validation of miRNAs is a tedious, time-consuming, and expensive process. Computational methods for miRNA gene detection are being developed so that the number of candidates that need experimental ...
Data mining for microrna gene prediction: On the impact of class imbalance and feature number for microrna gene prediction
(IEEE, 2013)
MicroRNAs (miRNAs) are small, non-coding RNAs which are involved in the posttranscriptional modulation of gene expression. Their short (18-24) single stranded mature sequences are involved in targeting specific genes. It ...
