Bayesian inference of the number of factors in gene-expression analysis: Application to human virus challenge studies

BMC Bioinformatics

Volumn 11, Issue , 2010, Pages

  Chen, Bo ^a   Chen, Minhua ^a   Paisley, John ^a   Zaas, Aimee ^b   Woods, Christopher ^b   Ginsburg, Geoffrey S ^b   Hero III, Alfred ^c   Lucas, Joseph ^b   Dunson, David ^d   Carin, Lawrence ^a  

^a Duke University   (United States)

^b DUKE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c UNIVERSITY OF MICHIGAN   (United States)

^d DUKE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN INFERENCE; INSTITUTIONAL REVIEW BOARDS; MATRIX DECOMPOSITION; MODEL PARAMETERS; NON-PARAMETRIC BAYESIAN; NUMBER OF FACTORS; RESPIRATORY SYNCYTIAL VIRUS; VARIATIONAL BAYESIAN;

BAYESIAN NETWORKS; FACTOR ANALYSIS; INFERENCE ENGINES; MULTIVARIANT ANALYSIS; VIRUSES;

GENE EXPRESSION;

RESPIRATORY SYNCYTIAL VIRUS; RHINOVIRUS;

ARTICLE; BAYES THEOREM; DNA MICROARRAY; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENETICS; HUMAN; METABOLISM; METHODOLOGY; ORTHOMYXOVIRUS; RESPIRATORY SYNCYTIAL PNEUMOVIRUS; RHINOVIRUS; VIRAL PHENOMENA AND FUNCTIONS;

BAYES THEOREM; GENE EXPRESSION; GENE EXPRESSION PROFILING; HUMANS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; ORTHOMYXOVIRIDAE; RESPIRATORY SYNCYTIAL VIRUSES; RHINOVIRUS; VIRUS PHYSIOLOGICAL PROCESSES;

EID: 78049501828     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-552     Document Type: Article

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