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Nucleic Acids Res. 2014 Dec 16;42(22):e167. doi: 10.1093/nar/gku918. Epub 2014 Oct 10.

ptRNApred: computational identification and classification of post-transcriptional RNA.

Author information

1
Department of Dermatology, University of Lübeck, 23538 Lübeck, Germany.
2
Department of Dermatology, University of Lübeck, 23538 Lübeck, Germany mareike.witte@medizin.uni-luebeck.de.
3
Institute for Molecular Medicine, University of Lübeck, 23538 Lübeck, Germany.
4
Department of Dermatology, University of Lübeck, 23538 Lübeck, Germany saleh.ibrahim@uk-sh.de.

Abstract

Non-coding RNAs (ncRNAs) are known to play important functional roles in the cell. However, their identification and recognition in genomic sequences remains challenging. In silico methods, such as classification tools, offer a fast and reliable way for such screening and multiple classifiers have already been developed to predict well-defined subfamilies of RNA. So far, however, out of all the ncRNAs, only tRNA, miRNA and snoRNA can be predicted with a satisfying sensitivity and specificity. We here present ptRNApred, a tool to detect and classify subclasses of non-coding RNA that are involved in the regulation of post-transcriptional modifications or DNA replication, which we here call post-transcriptional RNA (ptRNA). It (i) detects RNA sequences coding for post-transcriptional RNA from the genomic sequence with an overall sensitivity of 91% and a specificity of 94% and (ii) predicts ptRNA-subclasses that exist in eukaryotes: snRNA, snoRNA, RNase P, RNase MRP, Y RNA or telomerase RNA.

AVAILABILITY:

The ptRNApred software is open for public use on http://www.ptrnapred.org/.

PMID:
25303994
PMCID:
PMC4267668
DOI:
10.1093/nar/gku918
[Indexed for MEDLINE]
Free PMC Article

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