Cargando…
Differential co-expression framework to quantify goodness of biclusters and compare biclustering algorithms
BACKGROUND: Biclustering is an important analysis procedure to understand the biological mechanisms from microarray gene expression data. Several algorithms have been proposed to identify biclusters, but very little effort was made to compare the performance of different algorithms on real datasets...
Autores principales: | Chia, Burton Kuan Hui, Karuturi, R Krishna Murthy |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2010
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2892498/ https://www.ncbi.nlm.nih.gov/pubmed/20507637 http://dx.doi.org/10.1186/1748-7188-5-23 |
Ejemplares similares
-
A comparison and evaluation of five biclustering algorithms by quantifying goodness of biclusters for gene expression data
por: Li, Li, et al.
Publicado: (2012) -
A biclustering algorithm based on a Bicluster Enumeration Tree: application to DNA microarray data
por: Ayadi, Wassim, et al.
Publicado: (2009) -
Comparison of sparse biclustering algorithms for gene expression datasets
por: Nicholls, Kath, et al.
Publicado: (2021) -
Bi-Force: large-scale bicluster editing and its application to gene
expression data biclustering
por: Sun, Peng, et al.
Publicado: (2014) -
Multi-species integrative biclustering
por: Waltman, Peter, et al.
Publicado: (2010)