The t-mixture model approach for detecting differentially expressed genes in microarrays

Functional and Integrative Genomics

Volumn 8, Issue 3, 2008, Pages 181-186

  Jiao, Shuo ^a   Zhang, Shunpu ^a  

^a UNIVERSITY OF NEBRASKA LINCOLN   (United States)

Author keywords

Mixture; Normal mixture; Permutation

Indexed keywords

ARTICLE; CONTROLLED STUDY; DNA MICROARRAY; GENE EXPRESSION; GENE TECHNOLOGY; GENETIC ANALYSIS; GENETIC IDENTIFICATION; GENETIC VARIABILITY; INTERMETHOD COMPARISON; LEUKEMIA; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MIXTURE MODEL METHOD; NUCLEOTIDE SEQUENCE; PRIORITY JOURNAL; STATISTICAL MODEL; STATISTICS; T MIXTURE MODEL;

ALGORITHMS; COMPUTER SIMULATION; GENE EXPRESSION; GENOME, HUMAN; HUMANS; LEUKEMIA, MYELOID; LIKELIHOOD FUNCTIONS; MODELS, GENETIC; MODELS, STATISTICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PRECURSOR CELL LYMPHOBLASTIC LEUKEMIA-LYMPHOMA;

EID: 45449102465     PISSN: 1438793X     EISSN: 14387948     Source Type: Journal    
DOI: 10.1007/s10142-007-0071-6     Document Type: Article

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