Cargando…
ParaKMeans: Implementation of a parallelized K-means algorithm suitable for general laboratory use
BACKGROUND: During the last decade, the use of microarrays to assess the transcriptome of many biological systems has generated an enormous amount of data. A common technique used to organize and analyze microarray data is to perform cluster analysis. While many clustering algorithms have been devel...
Autores principales: | Kraj, Piotr, Sharma, Ashok, Garge, Nikhil, Podolsky, Robert, McIndoe, Richard A |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2008
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2375128/ https://www.ncbi.nlm.nih.gov/pubmed/18416829 http://dx.doi.org/10.1186/1471-2105-9-200 |
Ejemplares similares
-
ParaSAM: a parallelized version of the significance analysis of microarrays algorithm
por: Sharma, Ashok, et al.
Publicado: (2010) -
Fiber Clustering Acceleration With a Modified Kmeans++ Algorithm Using Data Parallelism
por: Goicovich, Isaac, et al.
Publicado: (2021) -
A modified hyperplane clustering algorithm allows for efficient and accurate clustering of extremely large datasets
por: Sharma, Ashok, et al.
Publicado: (2009) -
The IL-10 and IFN-γ pathways are essential to the potent immunosuppressive activity of cultured CD8(+ )NKT-like cells
por: Zhou, Li, et al.
Publicado: (2008) -
Random forest methodology for model-based recursive partitioning: the mobForest package for R
por: Garge, Nikhil R, et al.
Publicado: (2013)