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DisCons: a novel tool to quantify and classify evolutionary conservation of intrinsic protein disorder

Overview of attention for article published in BMC Bioinformatics, May 2015
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  • Good Attention Score compared to outputs of the same age (72nd percentile)

Mentioned by

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11 tweeters

Citations

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22 Dimensions

Readers on

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59 Mendeley
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2 CiteULike
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Title
DisCons: a novel tool to quantify and classify evolutionary conservation of intrinsic protein disorder
Published in
BMC Bioinformatics, May 2015
DOI 10.1186/s12859-015-0592-2
Pubmed ID
Authors

Mihaly Varadi, Mainak Guharoy, Fruzsina Zsolyomi, Peter Tompa

Abstract

Analyzing the amino acid sequence of an intrinsically disordered protein (IDP) in an evolutionary context can yield novel insights on the functional role of disordered regions and sequence element(s). However, in the case of many IDPs, the lack of evolutionary conservation of the primary sequence can hamper the study of functionality, because the conservation of their disorder profile and ensuing function(s) may not appear in a traditional analysis of the evolutionary history of the protein. Here we present DisCons (Disorder Conservation), a novel pipelined tool that combines the quantification of sequence- and disorder conservation to classify disordered residue positions. According to this scheme, the most interesting categories (for functional purposes) are constrained disordered residues and flexible disordered residues. The former residues show conservation of both the sequence and the property of disorder and are associated mainly with specific binding functionalities (e.g., short, linear motifs, SLiMs), whereas the latter class correspond to segments where disorder as a feature is important for function as opposed to the identity of the underlying sequence (e.g., entropic chains and linkers). DisCons therefore helps with elucidating the function(s) arising from the disordered state by analyzing individual proteins as well as large-scale proteomics datasets. DisCons is an openly accessible sequence analysis tool that identifies and highlights structurally disordered segments of proteins where the conformational flexibility is conserved across homologs, and therefore potentially functional. The tool is freely available both as a web application and as stand-alone source code hosted at http://pedb.vib.be/discons .

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 2%
Unknown 58 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 25%
Student > Ph. D. Student 12 20%
Student > Master 10 17%
Professor > Associate Professor 6 10%
Student > Bachelor 4 7%
Other 10 17%
Unknown 2 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 42%
Biochemistry, Genetics and Molecular Biology 19 32%
Computer Science 4 7%
Engineering 2 3%
Physics and Astronomy 1 2%
Other 2 3%
Unknown 6 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 19 May 2015.
All research outputs
#5,564,963
of 20,760,702 outputs
Outputs from BMC Bioinformatics
#2,186
of 6,827 outputs
Outputs of similar age
#65,975
of 244,566 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 1 outputs
Altmetric has tracked 20,760,702 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 6,827 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 67% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 244,566 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them