Title |
clusterMaker: a multi-algorithm clustering plugin for Cytoscape
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Published in |
BMC Bioinformatics, November 2011
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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
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 20% |
Unknown | 4 | 80% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 3 | 60% |
Members of the public | 2 | 40% |
Mendeley readers
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 | 483 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 123 | 24% |
Researcher | 105 | 20% |
Student > Master | 62 | 12% |
Student > Bachelor | 36 | 7% |
Student > Postgraduate | 28 | 5% |
Other | 76 | 15% |
Unknown | 83 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 181 | 35% |
Biochemistry, Genetics and Molecular Biology | 114 | 22% |
Computer Science | 44 | 9% |
Immunology and Microbiology | 16 | 3% |
Medicine and Dentistry | 16 | 3% |
Other | 51 | 10% |
Unknown | 91 | 18% |