Semi-supervised consensus clustering for gene expression data analysis

BACKGROUND: Simple clustering methods such as hierarchical clustering and k-means are widely used for gene expression data analysis; but they are unable to deal with noise and high dimensionality associated with the microarray gene expression data. Consensus clustering appears to improve the robustn...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Yunli, Pan, Youlian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Methodology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4036113/
https://www.ncbi.nlm.nih.gov/pubmed/24920961
http://dx.doi.org/10.1186/1756-0381-7-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4036113/
https://www.ncbi.nlm.nih.gov/pubmed/24920961
http://dx.doi.org/10.1186/1756-0381-7-7

Ejemplares similares