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clusterMaker: a multi-algorithm clustering plugin for Cytoscape

Overview of attention for article published in BMC Bioinformatics, November 2011
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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 (95th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
5 X users
patent
2 patents
wikipedia
1 Wikipedia page

Citations

dimensions_citation
503 Dimensions

Readers on

mendeley
510 Mendeley
citeulike
13 CiteULike
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Title
clusterMaker: a multi-algorithm clustering plugin for Cytoscape
Published in
BMC Bioinformatics, November 2011
DOI 10.1186/1471-2105-12-436
Pubmed ID
Authors

John H Morris, Leonard Apeltsin, Aaron M Newman, Jan Baumbach, Tobias Wittkop, Gang Su, Gary D Bader, Thomas E Ferrin

Abstract

In the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been clustered to identify stable complexes, but scientists lack easily accessible tools to facilitate combined analyses of multiple data sets from different types of experiments. Here we present clusterMaker, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram, and heat map views of the results. The Cytoscape network is linked to all of the other views, so that a selection in one is immediately reflected in the others. clusterMaker is the first Cytoscape plugin to implement such a wide variety of clustering algorithms and visualizations, including the only implementations of hierarchical clustering, dendrogram plus heat map visualization (tree view), k-means, k-medoid, SCPS, AutoSOME, and native (Java) MCL.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 510 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 1%
Germany 6 1%
United Kingdom 4 <1%
Netherlands 2 <1%
Chile 2 <1%
Canada 2 <1%
Korea, Republic of 1 <1%
India 1 <1%
France 1 <1%
Other 4 <1%
Unknown 480 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 123 24%
Researcher 105 21%
Student > Master 62 12%
Student > Bachelor 36 7%
Student > Postgraduate 28 5%
Other 74 15%
Unknown 82 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 180 35%
Biochemistry, Genetics and Molecular Biology 113 22%
Computer Science 44 9%
Immunology and Microbiology 16 3%
Medicine and Dentistry 16 3%
Other 51 10%
Unknown 90 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 02 November 2023.
All research outputs
#1,515,239
of 24,393,999 outputs
Outputs from BMC Bioinformatics
#246
of 7,529 outputs
Outputs of similar age
#7,065
of 146,520 outputs
Outputs of similar age from BMC Bioinformatics
#8
of 121 outputs
Altmetric has tracked 24,393,999 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,529 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 96% 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 146,520 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 95% of its contemporaries.
We're also able to compare this research output to 121 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.