PtRNApred: Computational Identification and Classification of Post-transcriptional RNA

Overview

Journal Nucleic Acids Res

Publisher Oxford University Press

Specialty Biochemistry

Date 2014 Oct 12

PMID 25303994

Citations 3

Authors

Yask Gupta

Mareike Witte

Steffen Moller

Ralf J Ludwig

Tobias Restle

Detlef Zillikens

Saleh M Ibrahim

Affiliations

Soon will be listed here.

Abstract

Unlabelled: 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/.

Citing Articles

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Ruy P, Monteiro-Teles N, Magalhaes R, Freitas-Castro F, Dias L, Defina T RNA Biol. 2019; 16(5):639-660.

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A Review on Recent Computational Methods for Predicting Noncoding RNAs.

Zhang Y, Huang H, Zhang D, Qiu J, Yang J, Wang K Biomed Res Int. 2017; 2017:9139504.

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