iSeeRNA: identification of long intergenic non-coding RNA transcripts from transcriptome sequencing data


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.



Published on: 2013-02-15

Made available via SpringerOpen / BioMedCentral. Please make sure to read our disclaimer prior to contacting 7thSpace Interactive. To contact our editors, visit our online helpdesk. To submit your press release click here.

Discussions




Custom Search

Username
Password










© 2016 7thSpace Interactive
All Rights Reserved - About | Disclaimer | Helpdesk