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Inferring homologous protein-protein interactions through pair position specific scoring matrix

Overview of attention for article published in BMC Bioinformatics, January 2013
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Title
Inferring homologous protein-protein interactions through pair position specific scoring matrix
Published in
BMC Bioinformatics, January 2013
DOI 10.1186/1471-2105-14-s2-s11
Pubmed ID
Authors

Chun-Yu Lin, Yung-Chiang Chen, Yu-Shu Lo, Jinn-Moon Yang

Abstract

The protein-protein interaction (PPI) is one of the most important features to understand biological processes. For a PPI, the physical domain-domain interaction (DDI) plays the key role for biology functions. In the post-genomic era, to rapidly identify homologous PPIs for analyzing the contact residue pairs of their interfaces within DDIs on a genomic scale is essential to determine PPI networks and the PPI interface evolution across multiple species.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 10%
Spain 1 5%
Unknown 18 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 33%
Student > Ph. D. Student 6 29%
Student > Master 3 14%
Student > Doctoral Student 2 10%
Other 2 10%
Other 1 5%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 33%
Agricultural and Biological Sciences 7 33%
Computer Science 5 24%
Engineering 1 5%
Unknown 1 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 23 January 2013.
All research outputs
#8,445,240
of 10,696,187 outputs
Outputs from BMC Bioinformatics
#3,494
of 4,171 outputs
Outputs of similar age
#215,508
of 308,172 outputs
Outputs of similar age from BMC Bioinformatics
#133
of 156 outputs
Altmetric has tracked 10,696,187 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,171 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 7th percentile – i.e., 7% 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 308,172 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 156 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.