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Predicting PDZ domain mediated protein interactions from structure

Overview of attention for article published in BMC Bioinformatics, January 2013
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  • Above-average Attention Score compared to outputs of the same age (60th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
5 tweeters

Citations

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22 Dimensions

Readers on

mendeley
64 Mendeley
citeulike
2 CiteULike
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Title
Predicting PDZ domain mediated protein interactions from structure
Published in
BMC Bioinformatics, January 2013
DOI 10.1186/1471-2105-14-27
Pubmed ID
Authors

Shirley Hui, Xiang Xing, Gary D Bader

Abstract

PDZ domains are structural protein domains that recognize simple linear amino acid motifs, often at protein C-termini, and mediate protein-protein interactions (PPIs) in important biological processes, such as ion channel regulation, cell polarity and neural development. PDZ domain-peptide interaction predictors have been developed based on domain and peptide sequence information. Since domain structure is known to influence binding specificity, we hypothesized that structural information could be used to predict new interactions compared to sequence-based predictors.

Twitter Demographics

The data shown below were collected from the profiles of 5 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 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Israel 1 2%
India 1 2%
Canada 1 2%
Spain 1 2%
Japan 1 2%
Unknown 59 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 27%
Researcher 17 27%
Student > Bachelor 6 9%
Student > Master 6 9%
Professor > Associate Professor 6 9%
Other 9 14%
Unknown 3 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 41%
Biochemistry, Genetics and Molecular Biology 18 28%
Medicine and Dentistry 4 6%
Engineering 3 5%
Computer Science 3 5%
Other 8 13%
Unknown 2 3%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 24 January 2013.
All research outputs
#7,393,715
of 14,571,674 outputs
Outputs from BMC Bioinformatics
#2,542
of 5,418 outputs
Outputs of similar age
#94,689
of 242,575 outputs
Outputs of similar age from BMC Bioinformatics
#95
of 189 outputs
Altmetric has tracked 14,571,674 research outputs across all sources so far. This one is in the 48th percentile – i.e., 48% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,418 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 51% 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 242,575 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 60% of its contemporaries.
We're also able to compare this research output to 189 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.