Abstract
micoRNA (miRNA) is a vital class of non-coding RNA genes, which participates in post-transcriptional gene regulation in eukaryotic cell. Interestingly, some close relationships between miRNA expression levels and several human diseases like cancers have been recently uncovered. Difficulties of identifying miRNAs via direct experimental method due to their special and temporal expression patterns make the computational prediction methods paramount important. Specially, non-comparative computational methods would have the advantage of recognizing species-specific miRNAs that can be missed by comparative methods. In this paper we present a systematic development of an improved classifier system for non-comparative human miRNA gene recognition using effective machine learning techniques.
Index
Terms
Available to subscribers and IEEE members.
References
Available to subscribers and IEEE members.
Citing Documents
Available to subscribers and IEEE members.
Cart
