CGBayesNets: Conditional Gaussian Bayesian Network Learning and Inference with Mixed Discrete and Continuous Data

PLoS Computational Biology

Volumn 10, Issue 6, 2014, Pages

  McGeachie, Michael J ^a,b   Chang, Hsun Hsien ^b,c   Weiss, Scott T ^a,b,d  

^a BRIGHAM AND WOMEN S HOSPITAL   (United States)

^b HARVARD MEDICAL SCHOOL   (United States)

^c BOSTON CHILDREN S HOSPITAL   (United States)

^d LABORATORY FOR MOLECULAR MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BARIUM COMPOUNDS; FORECASTING; GENE EXPRESSION; GENOME; INFERENCE ENGINES; INTENSIVE CARE UNITS; LEARNING ALGORITHMS; OPEN SOURCE SOFTWARE; OPEN SYSTEMS; TREES (MATHEMATICS);

BAYESIA N NETWORKS; BAYESIAN NETWORK INFERENCE; BAYESIAN NETWORK LEARNING; CONTINUOUS VARIABLES; GAUSSIANS; GENOMIC DATA; GENOMICS; METABOLOMICS; MIXED DISCRETE VARIABLES; PREDICTIVE MODELS;

MATLAB;

ARTICLE; BAYESIAN NETWORK; COMPUTER PROGRAM; DISEASE CLASSIFICATION; GENE EXPRESSION; GENOMICS; INTENSIVE CARE UNIT; LEARNING ALGORITHM; LEUKEMIA; MATHEMATICAL COMPUTING; METABOLOMICS; MORTALITY; PREDICTION; STATISTICAL CONCEPTS; STATISTICAL DISTRIBUTION; ALGORITHM; BAYES THEOREM; BIOLOGICAL MODEL; GENE EXPRESSION PROFILING; GENETICS; HUMAN; INTERNET; NORMAL DISTRIBUTION; PHENOTYPE; PROCEDURES; WOOD;

ALGORITHMS; BAYES THEOREM; GENE EXPRESSION PROFILING; GENOMICS; HUMANS; INTENSIVE CARE UNITS; INTERNET; LEUKEMIA; MODELS, BIOLOGICAL; NORMAL DISTRIBUTION; PHENOTYPE; SOFTWARE; WOOD;

EID: 84903398929     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1003676     Document Type: Article

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