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MultiSETTER: web server for multiple RNA structure comparison

Overview of attention for article published in BMC Bioinformatics, August 2015
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Title
MultiSETTER: web server for multiple RNA structure comparison
Published in
BMC Bioinformatics, August 2015
DOI 10.1186/s12859-015-0696-8
Pubmed ID
Authors

Petr Čech, David Hoksza, Daniel Svozil

Abstract

Understanding the architecture and function of RNA molecules requires methods for comparing and analyzing their tertiary and quaternary structures. While structural superposition of short RNAs is achievable in a reasonable time, large structures represent much bigger challenge. Therefore, we have developed a fast and accurate algorithm for RNA pairwise structure superposition called SETTER and implemented it in the SETTER web server. However, though biological relationships can be inferred by a pairwise structure alignment, key features preserved by evolution can be identified only from a multiple structure alignment. Thus, we extended the SETTER algorithm to the alignment of multiple RNA structures and developed the MultiSETTER algorithm. In this paper, we present the updated version of the SETTER web server that implements a user friendly interface to the MultiSETTER algorithm. The server accepts RNA structures either as the list of PDB IDs or as user-defined PDB files. After the superposition is computed, structures are visualized in 3D and several reports and statistics are generated. To the best of our knowledge, the MultiSETTER web server is the first publicly available tool for a multiple RNA structure alignment. The MultiSETTER server offers the visual inspection of an alignment in 3D space which may reveal structural and functional relationships not captured by other multiple alignment methods based either on a sequence or on secondary structure motifs.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 39%
Student > Bachelor 4 12%
Student > Ph. D. Student 4 12%
Student > Master 3 9%
Lecturer 1 3%
Other 4 12%
Unknown 4 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 39%
Agricultural and Biological Sciences 6 18%
Computer Science 4 12%
Medicine and Dentistry 3 9%
Chemistry 2 6%
Other 1 3%
Unknown 4 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 August 2015.
All research outputs
#17,768,879
of 22,821,814 outputs
Outputs from BMC Bioinformatics
#5,935
of 7,286 outputs
Outputs of similar age
#178,133
of 264,494 outputs
Outputs of similar age from BMC Bioinformatics
#93
of 117 outputs
Altmetric has tracked 22,821,814 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,286 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 13th percentile – i.e., 13% of its peers scored the same or lower than it.
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We're also able to compare this research output to 117 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.