Cargando…
Partial mixture model for tight clustering of gene expression time-course
BACKGROUND: Tight clustering arose recently from a desire to obtain tighter and potentially more informative clusters in gene expression studies. Scattered genes with relatively loose correlations should be excluded from the clusters. However, in the literature there is little work dedicated to this...
Autores principales: | Yuan, Yinyin, Li, Chang-Tsun, Wilson, Roland |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2008
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2492882/ https://www.ncbi.nlm.nih.gov/pubmed/18564420 http://dx.doi.org/10.1186/1471-2105-9-287 |
Ejemplares similares
-
Clustering of time-course gene expression profiles using normal mixture models with autoregressive random effects
por: Wang, Kui, et al.
Publicado: (2012) -
Prediction of heterogeneous differential genes by detecting outliers to a Gaussian tight cluster
por: Yang, Zihua, et al.
Publicado: (2013) -
Selection of reference genes for diurnal and developmental time-course real-time PCR expression analyses in lettuce
por: Sgamma, Tiziana, et al.
Publicado: (2016) -
h-Profile plots for the discovery and exploration of patterns in gene expression data with an application to time course data
por: Pittelkow, Yvonne E, et al.
Publicado: (2007) -
Difference-based clustering of short time-course microarray data with replicates
por: Kim, Jihoon, et al.
Publicado: (2007)