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Bioinformatics
Article . 2012 . Peer-reviewed
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Bioinformatics
Article
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Bioinformatics
Article . 2013
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Article . 2012
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Article . 2012
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Efficient RNA pairwise structure comparison by SETTER method

Authors: David Hoksza; Daniel Svozil;

Efficient RNA pairwise structure comparison by SETTER method

Abstract

AbstractMotivation: Understanding the architecture and function of RNA molecules requires methods for comparing and analyzing their 3D structures. Although a structural alignment of short RNAs is achievable in a reasonable amount of time, large structures represent much bigger challenge. However, the growth of the number of large RNAs deposited in the PDB database calls for the development of fast and accurate methods for analyzing their structures, as well as for rapid similarity searches in databases.Results: In this article a novel algorithm for an RNA structural comparison SETTER (SEcondary sTructure-based TERtiary Structure Similarity Algorithm) is introduced. SETTER uses a pairwise comparison method based on 3D similarity of the so-called generalized secondary structure units. For each pair of structures, SETTER produces a distance score and an indication of its statistical significance. SETTER can be used both for the structural alignments of structures that are already known to be homologous, as well as for 3D structure similarity searches and functional annotation. The algorithm presented is both accurate and fast and does not impose limits on the size of aligned RNA structures.Availability: The SETTER program, as well as all datasets, is freely available from http://siret.cz/hoksza/projects/setter/.Contact: hoksza@ksi.mff.cuni.cz, or svozild@vscht.czSupplementary information: Supplementary data are available at Bioinformatics online.

Related Organizations
Keywords

Sequence Analysis, RNA, Computational Biology, Nucleic Acid Conformation, RNA, Sequence Alignment, Algorithms, Software

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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