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Boolean implication networks derived from large scale, whole genome microarray datasets

We describe a method for extracting Boolean implications (if-then relationships) in very large amounts of gene expression microarray data. A meta-analysis of data from thousands of microarrays for humans, mice, and fruit flies finds millions of implication relationships between genes that would be m...

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Detalles Bibliográficos
Autores principales: Sahoo, Debashis, Dill, David L, Gentles, Andrew J, Tibshirani, Robert, Plevritis, Sylvia K
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2760884/
https://www.ncbi.nlm.nih.gov/pubmed/18973690
http://dx.doi.org/10.1186/gb-2008-9-10-r157
Descripción
Sumario:We describe a method for extracting Boolean implications (if-then relationships) in very large amounts of gene expression microarray data. A meta-analysis of data from thousands of microarrays for humans, mice, and fruit flies finds millions of implication relationships between genes that would be missed by other methods. These relationships capture gender differences, tissue differences, development, and differentiation. New relationships are discovered that are preserved across all three species.