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TMalphaDB and TMbetaDB: web servers to study the structural role of sequence motifs in α-helix and β-barrel domains of membrane proteins

Overview of attention for article published in BMC Bioinformatics, August 2015
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Title
TMalphaDB and TMbetaDB: web servers to study the structural role of sequence motifs in α-helix and β-barrel domains of membrane proteins
Published in
BMC Bioinformatics, August 2015
DOI 10.1186/s12859-015-0699-5
Pubmed ID
Authors

Marc Perea, Ivar Lugtenburg, Eduardo Mayol, Arnau Cordomí, Xavier Deupí, Leonardo Pardo, Mireia Olivella

Abstract

Membrane proteins represent over 25 % of human protein genes and account for more than 60 % of drug targets due to their accessibility from the extracellular environment. The increasing number of available crystal structures of these proteins in the Protein Data Bank permits an initial estimation of their structural properties. We have developed two web servers-TMalphaDB for α-helix bundles and TMbetaDB for β-barrels-to analyse the growing repertoire of available crystal structures of membrane proteins. TMalphaDB and TMbetaDB permit to search for these specific sequence motifs in a non-redundant structure database of transmembrane segments and quantify structural parameters such as ϕ and ψ backbone dihedral angles, χ1 side chain torsion angle, unit bend and unit twist. The structural information offered by TMalphaDB and TMbetaDB permits to quantify structural distortions induced by specific sequence motifs, and to elucidate their role in the 3D structure. This specific structural information has direct implications in homology modeling of the growing sequences of membrane proteins lacking experimental structure. TMalphaDB and TMbetaDB are freely available at http://lmc.uab.cat/TMalphaDB and http://lmc.uab.cat/TMbetaDB .

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 6%
Unknown 15 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 31%
Student > Bachelor 3 19%
Student > Ph. D. Student 2 13%
Student > Master 2 13%
Lecturer 1 6%
Other 1 6%
Unknown 2 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 44%
Biochemistry, Genetics and Molecular Biology 4 25%
Computer Science 3 19%
Unknown 2 13%
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 20 August 2015.
All research outputs
#17,770,433
of 22,824,164 outputs
Outputs from BMC Bioinformatics
#5,936
of 7,287 outputs
Outputs of similar age
#179,337
of 265,958 outputs
Outputs of similar age from BMC Bioinformatics
#96
of 122 outputs
Altmetric has tracked 22,824,164 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 7,287 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 122 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.