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Integrating protein-protein interaction networks with phenotypes reveals signs of interactions

Overview of attention for article published in Nature Methods, November 2013
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

blogs
1 blog
twitter
9 X users
wikipedia
1 Wikipedia page
f1000
1 research highlight platform

Citations

dimensions_citation
122 Dimensions

Readers on

mendeley
323 Mendeley
citeulike
9 CiteULike
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Title
Integrating protein-protein interaction networks with phenotypes reveals signs of interactions
Published in
Nature Methods, November 2013
DOI 10.1038/nmeth.2733
Pubmed ID
Authors

Arunachalam Vinayagam, Jonathan Zirin, Charles Roesel, Yanhui Hu, Bahar Yilmazel, Anastasia A Samsonova, Ralph A Neumüller, Stephanie E Mohr, Norbert Perrimon

Abstract

A major objective of systems biology is to organize molecular interactions as networks and to characterize information flow within networks. We describe a computational framework to integrate protein-protein interaction (PPI) networks and genetic screens to predict the 'signs' of interactions (i.e., activation-inhibition relationships). We constructed a Drosophila melanogaster signed PPI network consisting of 6,125 signed PPIs connecting 3,352 proteins that can be used to identify positive and negative regulators of signaling pathways and protein complexes. We identified an unexpected role for the metabolic enzymes enolase and aldo-keto reductase as positive and negative regulators of proteolysis, respectively. Characterization of the activation-inhibition relationships between physically interacting proteins within signaling pathways will affect our understanding of many biological functions, including signal transduction and mechanisms of disease.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 323 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 8 2%
United States 6 2%
Hungary 3 <1%
Germany 2 <1%
Italy 1 <1%
India 1 <1%
Austria 1 <1%
Netherlands 1 <1%
China 1 <1%
Other 3 <1%
Unknown 296 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 92 28%
Researcher 86 27%
Student > Bachelor 27 8%
Student > Master 26 8%
Professor 17 5%
Other 55 17%
Unknown 20 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 148 46%
Biochemistry, Genetics and Molecular Biology 48 15%
Computer Science 39 12%
Medicine and Dentistry 14 4%
Chemistry 8 2%
Other 37 11%
Unknown 29 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 13 December 2015.
All research outputs
#2,112,220
of 24,715,720 outputs
Outputs from Nature Methods
#2,241
of 5,237 outputs
Outputs of similar age
#23,625
of 313,888 outputs
Outputs of similar age from Nature Methods
#40
of 79 outputs
Altmetric has tracked 24,715,720 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,237 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.0. This one has gotten more attention than average, scoring higher than 57% 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 313,888 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.