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ProLego: tool for extracting and visualizing topological modules in protein structures

Overview of attention for article published in BMC Bioinformatics, May 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

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9 X users

Citations

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3 Dimensions

Readers on

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25 Mendeley
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2 CiteULike
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Title
ProLego: tool for extracting and visualizing topological modules in protein structures
Published in
BMC Bioinformatics, May 2018
DOI 10.1186/s12859-018-2171-9
Pubmed ID
Authors

Taushif Khan, Shailesh Kumar Panday, Indira Ghosh

Abstract

In protein design, correct use of topology is among the initial and most critical feature. Meticulous selection of backbone topology aids in drastically reducing the structure search space. With ProLego, we present a server application to explore the component aspect of protein structures and provide an intuitive and efficient way to scan the protein topology space. We have implemented in-house developed "topological representation" in an automated-pipeline to extract protein topology from given protein structure. Using the topology string, ProLego, compares topology against a non-redundant extensive topology database (ProLegoDB) as well as extracts constituent topological modules. The platform offers interactive topology visualization graphs. ProLego, provides an alternative but comprehensive way to scan and visualize protein topology along with an extensive database of protein topology. ProLego can be found at http://www.proteinlego.com.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 36%
Student > Ph. D. Student 4 16%
Student > Bachelor 2 8%
Professor 2 8%
Student > Postgraduate 2 8%
Other 3 12%
Unknown 3 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 36%
Agricultural and Biological Sciences 7 28%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Computer Science 1 4%
Physics and Astronomy 1 4%
Other 2 8%
Unknown 4 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 30 April 2019.
All research outputs
#5,122,942
of 24,840,108 outputs
Outputs from BMC Bioinformatics
#1,800
of 7,595 outputs
Outputs of similar age
#90,851
of 332,358 outputs
Outputs of similar age from BMC Bioinformatics
#21
of 106 outputs
Altmetric has tracked 24,840,108 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,595 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 75% 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 332,358 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 106 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.