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Bioinformatics. 2011 Jan 15;27(2):279-80. doi: 10.1093/bioinformatics/btq642. Epub 2010 Nov 13.

PLEXY: efficient target prediction for box C/D snoRNAs.

Author information

1
Department of Computer Science, University of Leipzig, Leipzig, Germany. steffi@bioinf.uni-leipzig.de

Abstract

MOTIVATION:

Small nucleolar RNAs (snoRNAs) are an abundant class of non-coding RNAs with a wide variety of cellular functions including chemical modification of RNA, telomere maintanance, pre-rRNA processing and regulatory activities in alternative splicing. The main role of box C/D snoRNAs is to determine the targets for 2'-O-ribose methylation, which is important for rRNA maturation and splicing regulation of some mRNAs. The targets are still unknown, however, for many 'orphan' snoRNAs. While a fast and efficient target predictor for box H/ACA snoRNAs is available, no comparable tool exists for box C/D snoRNAs, even though they bind to their targets in a much less complex manner.

RESULTS:

PLEXY is a dynamic programming algorithm that computes thermodynamically optimal interactions of a box C/D snoRNA with a putative target RNA. Implemented as scanner for large input sequences and equipped with filters on the duplex structure, PLEXY is an efficient and reliable tool for the prediction of box C/D snoRNA target sites.

AVAILABILITY:

The perl script PLEXY is freely available at http://www.bioinf.uni-leipzig.de/Software/PLEXY.

PMID:
21076148
DOI:
10.1093/bioinformatics/btq642
[Indexed for MEDLINE]

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