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Effective inter-residue contact definitions for accurate protein fold recognition

Overview of attention for article published in BMC Bioinformatics, January 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
9 tweeters

Citations

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22 Dimensions

Readers on

mendeley
43 Mendeley
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Title
Effective inter-residue contact definitions for accurate protein fold recognition
Published in
BMC Bioinformatics, January 2012
DOI 10.1186/1471-2105-13-292
Pubmed ID
Authors

Chao Yuan, Hao Chen, Daisuke Kihara

Abstract

Effective encoding of residue contact information is crucial for protein structure prediction since it has a unique role to capture long-range residue interactions compared to other commonly used scoring terms. The residue contact information can be incorporated in structure prediction in several different ways: It can be incorporated as statistical potentials or it can be also used as constraints in ab initio structure prediction. To seek the most effective definition of residue contacts for template-based protein structure prediction, we evaluated 45 different contact definitions, varying bases of contacts and distance cutoffs, in terms of their ability to identify proteins of the same fold.

Twitter Demographics

The data shown below were collected from the profiles of 9 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 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 5%
Canada 1 2%
India 1 2%
Belgium 1 2%
Spain 1 2%
Japan 1 2%
Unknown 36 84%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 35%
Researcher 12 28%
Professor > Associate Professor 5 12%
Student > Master 5 12%
Student > Postgraduate 3 7%
Other 3 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 40%
Biochemistry, Genetics and Molecular Biology 9 21%
Computer Science 6 14%
Chemistry 3 7%
Pharmacology, Toxicology and Pharmaceutical Science 2 5%
Other 4 9%
Unknown 2 5%

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 29 March 2013.
All research outputs
#2,130,364
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#967
of 4,588 outputs
Outputs of similar age
#23,356
of 137,422 outputs
Outputs of similar age from BMC Bioinformatics
#6
of 31 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,588 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 78% 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 137,422 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 31 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.