↓ Skip to main content

A methodology for detecting the orthology signal in a PPI network at a functional complex level

Overview of attention for article published in BMC Bioinformatics, June 2012
Altmetric Badge

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
19 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A methodology for detecting the orthology signal in a PPI network at a functional complex level
Published in
BMC Bioinformatics, June 2012
DOI 10.1186/1471-2105-13-s10-s18
Pubmed ID
Authors

Pavol Jancura, Eleftheria Mavridou, Enrique Carrillo-de Santa Pau, Elena Marchiori

Abstract

Stable evolutionary signal has been observed in a yeast protein-protein interaction (PPI) network. These finding suggests more connected regions of a PPI network to be potential mediators of evolutionary information. Because more connected regions of PPI networks contain functional complexes, we are motivated to exploit the orthology relation for identifying complexes that can be clearly attributed to such evolutionary signal.

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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 5%
United States 1 5%
Germany 1 5%
Brazil 1 5%
Unknown 15 79%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 37%
Student > Ph. D. Student 4 21%
Student > Bachelor 1 5%
Student > Doctoral Student 1 5%
Professor 1 5%
Other 3 16%
Unknown 2 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 42%
Computer Science 5 26%
Biochemistry, Genetics and Molecular Biology 2 11%
Medicine and Dentistry 1 5%
Unknown 3 16%

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 02 May 2013.
All research outputs
#10,995,630
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#4,226
of 4,588 outputs
Outputs of similar age
#120,125
of 143,968 outputs
Outputs of similar age from BMC Bioinformatics
#32
of 33 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,588 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 1st percentile – i.e., 1% 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 143,968 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.