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

ABSTRACT: 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.

SUBMITTER: Sahoo D 

PROVIDER: S-EPMC2760884 | biostudies-other | 2008 Oct

REPOSITORIES: biostudies-other

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

Sahoo Debashis D   Dill David L DL   Gentles Andrew J AJ   Tibshirani Robert R   Plevritis Sylvia K SK  

Genome biology 20081030 10

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 speci  ...[more]