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Prediction of protein interaction types based on sequence and network features

Overview of attention for article published in BMC Systems Biology, December 2013
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2 X users

Citations

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6 Dimensions

Readers on

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27 Mendeley
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Title
Prediction of protein interaction types based on sequence and network features
Published in
BMC Systems Biology, December 2013
DOI 10.1186/1752-0509-7-s6-s5
Pubmed ID
Authors

Florian Goebels, Dmitrij Frishman

Abstract

Protein interactions mediate a wide spectrum of functions in various cellular contexts. Functional versatility of protein complexes is due to a broad range of structural adaptations that determine their binding affinity, the number of interaction sites, and the lifetime. In terms of stability it has become customary to distinguish between obligate and non-obligate interactions dependent on whether or not the protomers can exist independently. In terms of spatio-temporal control protein interactions can be either simultaneously possible (SP) or mutually exclusive (ME). In the former case a network hub interacts with several proteins at the same time, offering each of them a separate interface, while in the latter case the hub interacts with its partners one at a time via the same binding site. So far different types of interactions were distinguished based on the properties of the corresponding binding interfaces derived from known three-dimensional structures of protein complexes.

X Demographics

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The data shown below were collected from the profiles of 2 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 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 4%
Unknown 26 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 26%
Researcher 6 22%
Student > Master 3 11%
Student > Postgraduate 2 7%
Professor 1 4%
Other 2 7%
Unknown 6 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 30%
Biochemistry, Genetics and Molecular Biology 5 19%
Computer Science 5 19%
Physics and Astronomy 1 4%
Medicine and Dentistry 1 4%
Other 1 4%
Unknown 6 22%
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 07 November 2014.
All research outputs
#16,722,190
of 25,374,917 outputs
Outputs from BMC Systems Biology
#613
of 1,132 outputs
Outputs of similar age
#197,898
of 320,433 outputs
Outputs of similar age from BMC Systems Biology
#24
of 47 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,132 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 42nd percentile – i.e., 42% 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 320,433 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.