Ontology highlight
ABSTRACT: Background
Long intergenic non-coding RNAs (lincRNAs) are emerging as a novel class of non-coding RNAs and potent gene regulators. High-throughput RNA-sequencing combined with de novo assembly promises quantity discovery of novel transcripts. However, the identification of lincRNAs from thousands of assembled transcripts is still challenging due to the difficulties of separating them from protein coding transcripts (PCTs).Results
We have implemented iSeeRNA, a support vector machine (SVM)-based classifier for the identification of lincRNAs. iSeeRNA shows better performance compared to other software. A public available webserver for iSeeRNA is also provided for small size dataset.Conclusions
iSeeRNA demonstrates high prediction accuracy and runs several magnitudes faster than other similar programs. It can be integrated into the transcriptome data analysis pipelines or run as a web server, thus offering a valuable tool for lincRNA study.
SUBMITTER: Sun K
PROVIDER: S-EPMC3582448 | biostudies-literature | 2013
REPOSITORIES: biostudies-literature
Sun Kun K Chen Xiaona X Jiang Peiyong P Song Xiaofeng X Wang Huating H Sun Hao H
BMC genomics 20130215
<h4>Background</h4>Long intergenic non-coding RNAs (lincRNAs) are emerging as a novel class of non-coding RNAs and potent gene regulators. High-throughput RNA-sequencing combined with de novo assembly promises quantity discovery of novel transcripts. However, the identification of lincRNAs from thousands of assembled transcripts is still challenging due to the difficulties of separating them from protein coding transcripts (PCTs).<h4>Results</h4>We have implemented iSeeRNA, a support vector mach ...[more]