Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology

BMC Bioinformatics

Volumn 13, Issue 1, 2012, Pages

  Hill, Steven M ^a,b   Neve, Richard M ^c   Bayani, Nora ^d   Kuo, Wen Lin ^d   Ziyad, Safiyyah ^d   Spellman, Paul T ^e   Gray, Joe W ^e   Mukherjee, Sach ^a,b  

^a NETHERLANDS CANCER INSTITUTE   (Netherlands)

^b UNIVERSITY OF WARWICK   (United Kingdom)

^c GENENTECH INC   (United States)

^d LAWRENCE BERKELEY NATIONAL LABORATORY   (United States)

^e OREGON HEALTH AND SCIENCE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN; BAYESIAN VARIABLE SELECTION; BIOCHEMICAL DATA; BIOLOGICAL INFORMATION; BIOLOGICAL RESPONSE; CANCER BIOLOGY; CANCER DRUG; EMPIRICAL BAYES; EMPIRICAL BAYES APPROACH; EMPIRICAL BAYES METHOD; EXACT INFERENCE; FREQUENTIST; INFORMATIVE PRIORS; INTERACTION TERM; MULTIPLE SOURCE; NETWORK MAPS; NETWORK-BASED; PRIOR INFORMATION; PRIOR KNOWLEDGE; RESPONSE DATA; SPARSITY CONSTRAINTS; STATISTICAL VARIABLES; VARIABLE SELECTION;

BAYESIAN NETWORKS;

ANTINEOPLASTIC AGENT; PHARMACOLOGICAL BIOMARKER;

ARTICLE; BAYES THEOREM; BIOLOGICAL MODEL; COMPUTER SIMULATION; HUMAN; METABOLISM; METHODOLOGY; NEOPLASM; PROBABILITY; STATISTICAL MODEL;

ANTINEOPLASTIC AGENTS; BAYES THEOREM; BIOMARKERS, PHARMACOLOGICAL; COMPUTER SIMULATION; HUMANS; LIKELIHOOD FUNCTIONS; MODELS, BIOLOGICAL; NEOPLASMS; PROBABILITY; RESEARCH DESIGN;

EID: 84860811237     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-13-94     Document Type: Article

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