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COGcollator: a web server for analysis of distant relationships between homologous protein families

Overview of attention for article published in Biology Direct, November 2017
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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 (74th percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
COGcollator: a web server for analysis of distant relationships between homologous protein families
Published in
Biology Direct, November 2017
DOI 10.1186/s13062-017-0198-x
Pubmed ID
Authors

Daria V. Dibrova, Kirill A. Konovalov, Vadim V. Perekhvatov, Konstantin V. Skulachev, Armen Y. Mulkidjanian

Abstract

The Clusters of Orthologous Groups (COGs) of proteins systematize evolutionary related proteins into specific groups with similar functions. However, the available databases do not provide means to assess the extent of similarity between the COGs. We intended to provide a method for identification and visualization of evolutionary relationships between the COGs, as well as a respective web server. Here we introduce the COGcollator, a web tool for identification of evolutionarily related COGs and their further analysis. We demonstrate the utility of this tool by identifying the COGs that contain distant homologs of (i) the catalytic subunit of bacterial rotary membrane ATP synthases and (ii) the DNA/RNA helicases of the superfamily 1. This article was reviewed by Drs. Igor N. Berezovsky, Igor Zhulin and Yuri Wolf.

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X Demographics

The data shown below were collected from the profiles of 12 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 13%
Student > Master 2 13%
Professor > Associate Professor 2 13%
Professor 1 7%
Researcher 1 7%
Other 1 7%
Unknown 6 40%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 33%
Computer Science 2 13%
Agricultural and Biological Sciences 1 7%
Immunology and Microbiology 1 7%
Psychology 1 7%
Other 1 7%
Unknown 4 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 28 March 2018.
All research outputs
#6,010,999
of 24,226,848 outputs
Outputs from Biology Direct
#203
of 513 outputs
Outputs of similar age
#110,987
of 446,794 outputs
Outputs of similar age from Biology Direct
#6
of 8 outputs
Altmetric has tracked 24,226,848 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 513 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has gotten more attention than average, scoring higher than 60% 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 446,794 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 74% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.