Regularized estimation of large-scale gene association networks using graphical Gaussian models

BACKGROUND: Graphical Gaussian models are popular tools for the estimation of (undirected) gene association networks from microarray data. A key issue when the number of variables greatly exceeds the number of samples is the estimation of the matrix of partial correlations. Since the (Moore-Penrose)...

Descripción completa

Detalles Bibliográficos
Autores principales: Krämer, Nicole, Schäfer, Juliane, Boulesteix, Anne-Laure
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Research article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808166/
https://www.ncbi.nlm.nih.gov/pubmed/19930695
http://dx.doi.org/10.1186/1471-2105-10-384

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808166/
https://www.ncbi.nlm.nih.gov/pubmed/19930695
http://dx.doi.org/10.1186/1471-2105-10-384

Ejemplares similares