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BioShell-Threading: versatile Monte Carlo package for protein 3D threading

Overview of attention for article published in BMC Bioinformatics, January 2014
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Mentioned by

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3 X users
facebook
1 Facebook page

Citations

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17 Dimensions

Readers on

mendeley
23 Mendeley
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2 CiteULike
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Title
BioShell-Threading: versatile Monte Carlo package for protein 3D threading
Published in
BMC Bioinformatics, January 2014
DOI 10.1186/1471-2105-15-22
Pubmed ID
Authors

Pawel Gniewek, Andrzej Kolinski, Andrzej Kloczkowski, Dominik Gront

Abstract

The comparative modeling approach to protein structure prediction inherently relies on a template structure. Before building a model such a template protein has to be found and aligned with the query sequence. Any error made on this stage may dramatically affects the quality of result. There is a need, therefore, to develop accurate and sensitive alignment protocols.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 35%
Student > Bachelor 3 13%
Student > Postgraduate 3 13%
Student > Master 3 13%
Researcher 2 9%
Other 3 13%
Unknown 1 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 26%
Biochemistry, Genetics and Molecular Biology 4 17%
Computer Science 4 17%
Pharmacology, Toxicology and Pharmaceutical Science 2 9%
Medicine and Dentistry 2 9%
Other 4 17%
Unknown 1 4%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 22 January 2014.
All research outputs
#14,102,908
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#4,294
of 7,454 outputs
Outputs of similar age
#167,598
of 311,341 outputs
Outputs of similar age from BMC Bioinformatics
#51
of 94 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,454 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
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 311,341 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 94 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.