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Visualization of protein interaction networks: problems and solutions

Overview of attention for article published in BMC Bioinformatics, January 2013
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

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3 X users
patent
1 patent

Citations

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64 Dimensions

Readers on

mendeley
167 Mendeley
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7 CiteULike
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Title
Visualization of protein interaction networks: problems and solutions
Published in
BMC Bioinformatics, January 2013
DOI 10.1186/1471-2105-14-s1-s1
Pubmed ID
Authors

Giuseppe Agapito, Pietro Hiram Guzzi, Mario Cannataro

Abstract

Visualization concerns the representation of data visually and is an important task in scientific research. Protein-protein interactions (PPI) are discovered using either wet lab techniques, such mass spectrometry, or in silico predictions tools, resulting in large collections of interactions stored in specialized databases. The set of all interactions of an organism forms a protein-protein interaction network (PIN) and is an important tool for studying the behaviour of the cell machinery. Since graphic representation of PINs may highlight important substructures, e.g. protein complexes, visualization is more and more used to study the underlying graph structure of PINs. Although graphs are well known data structures, there are different open problems regarding PINs visualization: the high number of nodes and connections, the heterogeneity of nodes (proteins) and edges (interactions), the possibility to annotate proteins and interactions with biological information extracted by ontologies (e.g. Gene Ontology) that enriches the PINs with semantic information, but complicates their visualization.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 167 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 2%
Germany 3 2%
United Kingdom 2 1%
Colombia 1 <1%
Brazil 1 <1%
Portugal 1 <1%
India 1 <1%
Japan 1 <1%
Luxembourg 1 <1%
Other 0 0%
Unknown 152 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 43 26%
Researcher 40 24%
Student > Master 28 17%
Student > Bachelor 12 7%
Professor 6 4%
Other 14 8%
Unknown 24 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 53 32%
Biochemistry, Genetics and Molecular Biology 26 16%
Computer Science 25 15%
Medicine and Dentistry 9 5%
Social Sciences 5 3%
Other 20 12%
Unknown 29 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 09 June 2022.
All research outputs
#6,392,102
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#2,377
of 7,400 outputs
Outputs of similar age
#67,695
of 288,111 outputs
Outputs of similar age from BMC Bioinformatics
#49
of 136 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 7,400 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 67% 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 288,111 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 136 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 63% of its contemporaries.