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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)...
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| Main Authors: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2009
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2808166/ https://ncbi.nlm.nih.gov/pubmed/19930695 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-10-384 |
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