Using hidden Markov models to analyze gene expression time course data

Bioinformatics

Volumn 19, Issue SUPPL. 1, 2003, Pages

  Schliep, Alexander ^a   Schönhuth, Alexander ^b   Steinhoff, Christine ^a  

^a MAX PLANCK INSTITUTE FOR MOLECULAR GENETICS   (Germany)

^b UNIVERSITY OF COLOGNE   (Germany)

Author keywords

Gene Expression; Hidden Markov models; Model based clustering; Time course

Indexed keywords

COMPUTER INTERFACE; CONFERENCE PAPER; GENE EXPRESSION; MATHEMATICAL MODEL; PRIORITY JOURNAL; PROBABILITY; TIME; ALGORITHM; ARTICLE; BIOLOGICAL MODEL; CELL CYCLE; CLUSTER ANALYSIS; COMPARATIVE STUDY; COMPUTER PROGRAM; CYTOLOGY; EVALUATION; FIBROBLAST; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETICS; METABOLISM; METHODOLOGY; PHYSIOLOGY; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS; STATISTICAL MODEL; VALIDATION STUDY; YEAST;

PROTEIN;

ALGORITHMS; CELL CYCLE; CLUSTER ANALYSIS; FIBROBLASTS; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; MARKOV CHAINS; MODELS, GENETIC; MODELS, STATISTICAL; PROTEINS; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, PROTEIN; SOFTWARE; TIME FACTORS; USER-COMPUTER INTERFACE; YEASTS;

EID: 4944252468     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btg1036     Document Type: Conference Paper

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