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Arena3D: visualizing time-driven phenotypic differences in biological systems

Overview of attention for article published in BMC Bioinformatics, March 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)

Mentioned by

twitter
8 tweeters
googleplus
1 Google+ user

Readers on

mendeley
63 Mendeley
citeulike
1 CiteULike
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Title
Arena3D: visualizing time-driven phenotypic differences in biological systems
Published in
BMC Bioinformatics, March 2012
DOI 10.1186/1471-2105-13-45
Pubmed ID
Authors

Maria Secrier, Georgios A Pavlopoulos, Jan Aerts, Reinhard Schneider

Abstract

Elucidating the genotype-phenotype connection is one of the big challenges of modern molecular biology. To fully understand this connection, it is necessary to consider the underlying networks and the time factor. In this context of data deluge and heterogeneous information, visualization plays an essential role in interpreting complex and dynamic topologies. Thus, software that is able to bring the network, phenotypic and temporal information together is needed. Arena3D has been previously introduced as a tool that facilitates link discovery between processes. It uses a layered display to separate different levels of information while emphasizing the connections between them. We present novel developments of the tool for the visualization and analysis of dynamic genotype-phenotype landscapes.

Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters 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 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Luxembourg 2 3%
Germany 2 3%
United States 2 3%
Brazil 2 3%
Canada 1 2%
Switzerland 1 2%
Portugal 1 2%
Unknown 52 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 40%
Student > Ph. D. Student 8 13%
Professor > Associate Professor 7 11%
Student > Bachelor 6 10%
Professor 4 6%
Other 11 17%
Unknown 2 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 44%
Computer Science 14 22%
Biochemistry, Genetics and Molecular Biology 9 14%
Engineering 3 5%
Physics and Astronomy 1 2%
Other 3 5%
Unknown 5 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 17 January 2018.
All research outputs
#2,105,417
of 12,379,581 outputs
Outputs from BMC Bioinformatics
#946
of 4,594 outputs
Outputs of similar age
#19,442
of 117,262 outputs
Outputs of similar age from BMC Bioinformatics
#2
of 4 outputs
Altmetric has tracked 12,379,581 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,594 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 79% 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 117,262 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 83% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.