Fitting Boolean networks from steady state perturbation data

Statistical Applications in Genetics and Molecular Biology

Volumn 10, Issue 1, 2011, Pages

  Almudevar, Anthony ^a   McCall, Matthew N ^a   McMurray, Helene ^a   Land, Hartmut ^a  

^a UNIVERSITY OF ROCHESTER   (United States)

Author keywords

Bayesian modeling; boolean network; gene perturbation

Indexed keywords

ALGORITHM; ARTICLE; BAYES THEOREM; BOOLEAN TETWORK; CANCER CELL; GENE PERTURBATION; GENE REGULATORY NETWORK; GENETIC ANALYSIS; METHODOLOGY; STATISTICAL ANALYSIS; STEADY STATE; TUMOR GENE;

ALGORITHMS; ANIMALS; BAYES THEOREM; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; GENE REGULATORY NETWORKS; GENES, NEOPLASM; GENETICS, POPULATION; HUMANS; MARKOV CHAINS; MODELS, GENETIC; MONTE CARLO METHOD; MUTATION; NEOPLASMS; PREDICTIVE VALUE OF TESTS; REPRODUCIBILITY OF RESULTS;

EID: 80455132486     PISSN: None     EISSN: 15446115     Source Type: Journal    
DOI: 10.2202/1544-6115.1727     Document Type: Article

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