Software
ParaKMeans: Implementation of a parallelized K-means algorithm suitable for general laboratory use
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* Corresponding author: Richard A McIndoe rmcindoe@mail.mcg.edu
- † Equal contributors
Center for Biotechnology and Genomic Medicine, Medical College of Georgia, Augusta, GA USA
BMC Bioinformatics 2008, 9:200 doi:10.1186/1471-2105-9-200
Published: 16 April 2008Additional files
Additional file 1:
Speedup results for the four cluster simulated data using 35, 100 and 200 arrays. For each plot, the y-axis is the speedup value and the x-axis is the number of nodes used to run ParaKMeans. Each line is a different number of genes clustered in that dataset.
Format: PPT Size: 204KB Download file
This file can be viewed with: Microsoft PowerPoint Viewer
Additional file 2:
Speedup results for the ten cluster simulated data using 35, 100 and 200 arrays. For each plot, the y-axis is the speedup value and the x-axis is the number of nodes used to run ParaKMeans. Each line is a different number of genes clustered in that dataset.
Format: PPT Size: 204KB Download file
This file can be viewed with: Microsoft PowerPoint Viewer
Additional file 3:
Speedup results for the twenty cluster simulated data using 35, 100 and 200 arrays. For each plot, the y-axis is the speedup value and the x-axis is the number of nodes used to run ParaKMeans. Each line is a different number of genes clustered in that dataset.
Format: PPT Size: 205KB Download file
This file can be viewed with: Microsoft PowerPoint Viewer
Additional file 4:
ParaKMeans Help system. The Windows Help file contains a description of the program, installation instructions, tutorials and the API documentation.
Format: PPT Size: 221KB Download file
This file can be viewed with: Microsoft PowerPoint Viewer
Additional file 5:
ParaKMeans windows help file. This file is a windows help file (.chm) that provides a more detailed overview of the software, installation instructions, program tutorials, the ParaKMeans API and troubleshooting help.
Format: CHM Size: 3MB Download file