Japan Bioinformatics

Simbiot implements a total of 6 different clustering algorithms. Each algorithm type (k-means, self-organizing maps and Hierarchical) is implemented twice – once using Cluster 3.0 (de Hoon, Imoto et al. 2004) function and once using R built-in functions. Principal component analysis (PCA) is implemented using standard R functions; the data may be analyzed directly or following k-means or SOM clustering.

 

Algorithm	Implementation	Further Information
k-means, SOM, PCA, Hierarchical	Cluster 3.0	http://bonsai.ims.u-tokyo.ac.jp/~mdehoon/software/cluster/cluster3.pdf
k-means	R	http://stat.ethz.ch/R-manual/R-patched/library/stats/html/kmeans.html
SOM	R	http://cran.r-project.org/web/packages/som/index.html
Hierarchical	R	http://stat.ethz.ch/R-manual/R-patched/library/stats/html/hclust.html

 

References

de Hoon, M. J., S. Imoto, et al. (2004). “Open source clustering software.” Bioinformatics 20(9): 1453-4.

 

Selected screen shots