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DeDaL: Cytoscape 3 app for producing and morphing data-driven and structure-driven network layouts

Overview of attention for article published in BMC Systems Biology, August 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

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Citations

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17 Dimensions

Readers on

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33 Mendeley
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2 CiteULike
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Title
DeDaL: Cytoscape 3 app for producing and morphing data-driven and structure-driven network layouts
Published in
BMC Systems Biology, August 2015
DOI 10.1186/s12918-015-0189-4
Pubmed ID
Authors

Urszula Czerwinska, Laurence Calzone, Emmanuel Barillot, Andrei Zinovyev

Abstract

Visualization and analysis of molecular profiling data together with biological networks are able to provide new mechanistic insights into biological functions. Currently, it is possible to visualize high-throughput data on top of pre-defined network layouts, but they are not always adapted to a given data analysis task. A network layout based simultaneously on the network structure and the associated multidimensional data might be advantageous for data visualization and analysis in some cases. We developed a Cytoscape app, which allows constructing biological network layouts based on the data from molecular profiles imported as values of node attributes. DeDaL is a Cytoscape 3 app, which uses linear and non-linear algorithms of dimension reduction to produce data-driven network layouts based on multidimensional data (typically gene expression). DeDaL implements several data pre-processing and layout post-processing steps such as continuous morphing between two arbitrary network layouts and aligning one network layout with respect to another one by rotating and mirroring. The combination of all these functionalities facilitates the creation of insightful network layouts representing both structural network features and correlation patterns in multivariate data. We demonstrate the added value of applying DeDaL in several practical applications, including an example of a large protein-protein interaction network. DeDaL is a convenient tool for applying data dimensionality reduction methods and for designing insightful data displays based on data-driven layouts of biological networks, built within Cytoscape environment. DeDaL is freely available for downloading at http://bioinfo-out.curie.fr/projects/dedal/ .

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 3%
Italy 1 3%
Singapore 1 3%
Brazil 1 3%
Unknown 29 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 48%
Student > Ph. D. Student 5 15%
Student > Master 3 9%
Student > Bachelor 2 6%
Professor > Associate Professor 2 6%
Other 1 3%
Unknown 4 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 33%
Biochemistry, Genetics and Molecular Biology 6 18%
Computer Science 4 12%
Environmental Science 2 6%
Chemical Engineering 1 3%
Other 1 3%
Unknown 8 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 28 March 2016.
All research outputs
#13,210,525
of 22,821,814 outputs
Outputs from BMC Systems Biology
#451
of 1,142 outputs
Outputs of similar age
#120,956
of 264,379 outputs
Outputs of similar age from BMC Systems Biology
#13
of 32 outputs
Altmetric has tracked 22,821,814 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one has gotten more attention than average, scoring higher than 58% 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 264,379 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 32 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 56% of its contemporaries.