Learning Gaussian graphical models of gene networks with false discovery rate control

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4973 LNCS, Issue , 2008, Pages 165-176

  Peña, Jose M ^a  

^a LINKÖPING UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

ADMINISTRATIVE DATA PROCESSING; ARTIFICIAL INTELLIGENCE; BIOCOMMUNICATIONS; BIOINFORMATICS; BOOLEAN FUNCTIONS; DATA MINING; DECISION SUPPORT SYSTEMS; EDUCATION; GENE EXPRESSION; GRAPHIC METHODS; INFORMATION MANAGEMENT; INFORMATION SCIENCE; KNOWLEDGE MANAGEMENT; LEARNING SYSTEMS; MINING; OPTIMAL CONTROL SYSTEMS; ROBOT LEARNING; SEARCH ENGINES; TRELLIS CODES;

EUROPEAN; EVOLUTIONARY COMPUTATION (EC); FALSE DISCOVERY RATE (FDR); GAUSSIAN; GENE EXPRESSION (MICROARRAY) DATA; GENE NETWORK (GN); GRAPHICAL MODELS (GM); HEIDELBERG (CO); MACHINE-LEARNING; ROSETTA;

LEARNING ALGORITHMS;

EID: 47249137432     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-78757-0_15     Document Type: Conference Paper

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