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Medusa: A tool for exploring and clustering biological networks

Overview of attention for article published in BMC Research Notes, October 2011
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Mentioned by

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1 tweeter

Citations

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40 Dimensions

Readers on

mendeley
59 Mendeley
citeulike
3 CiteULike
Title
Medusa: A tool for exploring and clustering biological networks
Published in
BMC Research Notes, October 2011
DOI 10.1186/1756-0500-4-384
Pubmed ID
Authors

Georgios A Pavlopoulos, Sean D Hooper, Alejandro Sifrim, Reinhard Schneider, Jan Aerts

Abstract

Biological processes such as metabolic pathways, gene regulation or protein-protein interactions are often represented as graphs in systems biology. The understanding of such networks, their analysis, and their visualization are today important challenges in life sciences. While a great variety of visualization tools that try to address most of these challenges already exists, only few of them succeed to bridge the gap between visualization and network analysis.

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

Geographical breakdown

Country Count As %
Germany 2 3%
Belgium 2 3%
Luxembourg 2 3%
Finland 1 2%
United Kingdom 1 2%
Unknown 51 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 27%
Student > Ph. D. Student 14 24%
Student > Master 6 10%
Professor > Associate Professor 5 8%
Professor 3 5%
Other 12 20%
Unknown 3 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 49%
Computer Science 10 17%
Biochemistry, Genetics and Molecular Biology 8 14%
Medicine and Dentistry 2 3%
Social Sciences 2 3%
Other 4 7%
Unknown 4 7%

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 18 July 2014.
All research outputs
#3,056,053
of 4,507,509 outputs
Outputs from BMC Research Notes
#879
of 1,369 outputs
Outputs of similar age
#72,686
of 109,629 outputs
Outputs of similar age from BMC Research Notes
#75
of 98 outputs
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So far Altmetric has tracked 1,369 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 24th percentile – i.e., 24% 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 109,629 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 98 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.