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Local Network Patterns in Protein-Protein Interfaces

Overview of attention for article published in PLOS ONE, March 2013
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36 Mendeley
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2 CiteULike
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Title
Local Network Patterns in Protein-Protein Interfaces
Published in
PLOS ONE, March 2013
DOI 10.1371/journal.pone.0057031
Pubmed ID
Authors

Qiang Luo, Rebecca Hamer, Gesine Reinert, Charlotte M. Deane

Abstract

Protein-protein interfaces hold the key to understanding protein-protein interactions. In this paper we investigated local interaction network patterns beyond pair-wise contact sites by considering interfaces as contact networks among residues. A contact site was defined as any residue on the surface of one protein which was in contact with a residue on the surface of another protein. We labeled the sub-graphs of these contact networks by their amino acid types. The observed distributions of these labeled sub-graphs were compared with the corresponding background distributions and the results suggested that there were preferred chemical patterns of closely packed residues at the interface. These preferred patterns point to biological constraints on physical proximity between those residues on one protein which were involved in binding to residues which were close on the interacting partner. Interaction interfaces were far from random and contain information beyond pairs and triangles. To illustrate the possible application of the local network patterns observed, we introduced a signature method, called iScore, based on these local patterns to assess interface predictions. On our data sets iScore achieved 83.6% specificity with 82% sensitivity.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 6%
Japan 1 3%
Portugal 1 3%
Unknown 32 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 36%
Researcher 9 25%
Student > Master 4 11%
Student > Doctoral Student 3 8%
Other 2 6%
Other 4 11%
Unknown 1 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 33%
Biochemistry, Genetics and Molecular Biology 6 17%
Computer Science 4 11%
Chemistry 3 8%
Physics and Astronomy 2 6%
Other 6 17%
Unknown 3 8%
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 01 June 2015.
All research outputs
#14,431,072
of 23,577,654 outputs
Outputs from PLOS ONE
#119,768
of 202,026 outputs
Outputs of similar age
#111,409
of 197,001 outputs
Outputs of similar age from PLOS ONE
#2,830
of 5,444 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 202,026 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.3. 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 197,001 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5,444 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.