PtRNApred: Computational identification and classification of post-transcriptional RNA

Yask Gupta, Mareike Witte, Steffen Möller, Ralf J. Ludwig, Tobias Restle, Detlef Zillikens, Saleh M. Ibrahim

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

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 silicomethods, 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/.

Original languageBritish English
Article numbere167
JournalNucleic Acids Research
Volume42
Issue number22
DOIs
StatePublished - 16 Dec 2014

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