Identifying pathogenic processes by integrating microarray data with prior knowledge

BMC Bioinformatics

Volumn 15, Issue 1, 2014, Pages

  Nygård, Ståle ^a,b   Reitan, Trond ^b   Clancy, Trevor ^a   Nygaard, Vegard ^a   Bjørnstad, Johannes ^a,b   Skrbic, Biljana ^a,b   Tønnessen, Theis ^a,b   Christensen, Geir ^a,b   Hovig, Eivind ^a,b  

^a OSLO UNIVERSITY HOSPITAL   (Norway)

^b UNIVERSITY OF OSLO   (Norway)

Author keywords

[No Author keywords available]

Indexed keywords

MONTE CARLO METHODS;

BAYESIAN STATISTICS; CARBOHYDRATE METABOLISM; DIFFERENTIALLY EXPRESSED GENE; EXTERNAL INFORMATIONS; EXTRACELLULAR MATRICES; HIGH-THROUGHPUT METHOD; MARKOV CHAIN MONTE CARLO SAMPLINGS; TRADITIONAL CLUSTERING;

GENES;

TRANSCRIPTION FACTOR;

ALGORITHM; ANIMAL; ARTICLE; BAYES THEOREM; CLUSTER ANALYSIS; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORK; GENETICS; HEART FAILURE; HUMAN; MELANOMA; METABOLISM; METHODOLOGY; MONTE CARLO METHOD; MOUSE; PROBABILITY; PROTEIN ANALYSIS; SEQUENCE HOMOLOGY;

ALGORITHMS; ANIMALS; BAYES THEOREM; CLUSTER ANALYSIS; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORKS; HEART FAILURE; HUMANS; MARKOV CHAINS; MELANOMA; MICE; MONTE CARLO METHOD; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PROTEIN INTERACTION MAPPING; SEQUENCE HOMOLOGY, AMINO ACID; TRANSCRIPTION FACTORS;

EID: 84899955748     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-15-115     Document Type: Article

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