Determining transcription factor activity from microarray data using bayesian markov chain monte carlo sampling

Studies in Health Technology and Informatics

Volumn 129, Issue , 2007, Pages 1250-1254

  Kossenkov, Andrew V ^a   Peterson, Aidan J ^b   Ochs, Michael F ^c  

^a WISTAR INSTITUTE   (United States)

^b UNIVERSITY OF MINNESOTA   (United States)

^c JOHNS HOPKINS UNIVERSITY   (United States)

Author keywords

Bayesian analysis; Microarray analysis; transcription factors

Indexed keywords

BIOINFORMATICS; FACTOR ANALYSIS; MARKOV PROCESSES; MONTE CARLO METHODS; PROBABILITY DISTRIBUTIONS; TRANSCRIPTION FACTORS; YEAST;

BAYESIAN ANALYSIS; BAYESIAN MARKOV CHAIN MONTE CARLO; BIOLOGICAL PROCESS; BIOLOGICAL RESPONSE; MICROARRAY ANALYSIS; TRANSCRIPTIONAL REGULATOR; TRANSCRIPTIONAL RESPONSE; YEAST CELL CYCLES;

TRANSCRIPTION;

TRANSCRIPTION FACTOR;

ALGORITHM; ARTICLE; BAYES THEOREM; BIOLOGICAL MODEL; BIOLOGY; DNA MICROARRAY; GENE EXPRESSION REGULATION; GENETIC TRANSCRIPTION; GENETICS; METABOLISM; MONTE CARLO METHOD; PROBABILITY; ROC CURVE; YEAST;

ALGORITHMS; BAYES THEOREM; COMPUTATIONAL BIOLOGY; GENE EXPRESSION REGULATION; MARKOV CHAINS; MODELS, GENETIC; MONTE CARLO METHOD; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; ROC CURVE; TRANSCRIPTION FACTORS; TRANSCRIPTION, GENETIC; YEASTS;

EID: 35748970508     PISSN: 09269630     EISSN: 18798365     Source Type: Book Series    
DOI: None     Document Type: Conference Paper

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