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A machine learning approach for microRNA precursor prediction in retro-transcribing virus genomes
(Walter De Gruyter, 2016-12)
Identification of microRNA (miRNA) precursors has seen increased efforts in recent years. The difficulty in experimental detection of pre-miRNAs increased the usage of computational approaches. Most of these approaches ...
PGMiner reloaded, fully automated proteogenomic annotation tool linking genomes to proteomes
(De Gruyter, 2016)
Improvements in genome sequencing technology increased the availability of full genomes and transcriptomes of many organisms. However, the major benefit of massive parallel sequencing is to better understand the organization ...
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 ...
One step forward, two steps back; Xeno-MicroRNAs reported in breast milk are artifacts
(Public Library of Science, 2016-01)
Background: MicroRNAs (miRNAs) are short RNA sequences that guide post-transcriptional regulation of gene expression via complementarity to their target mRNAs. Discovered only recently, miRNAs have drawn a lot of attention. ...
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 ...
