Gene expression data analysis using a novel approach to biclustering combining discrete and continuous data

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 5, Issue 4, 2008, Pages 583-593

  Christinat, Yann ^a   Wachmann, Bernd ^a   Zhang, Lei ^a  

^a EPFL   (Switzerland)

Author keywords

Biclustering algorithm; Data mining; Discrete data; Gene expression data; Microarray analysis; Simultaneous clustering

Indexed keywords

BICLUSTERING ALGORITHM; DISCRETE DATA; GENE EXPRESSION DATA; MICROARRAY ANALYSIS; SIMULTANEOUS CLUSTERING;

ALGORITHMS; BIOACTIVITY; BIOASSAY; CLUSTERING ALGORITHMS; COLUMNS (STRUCTURAL); DECISION SUPPORT SYSTEMS; GENE EXPRESSION; HEURISTIC METHODS; INFORMATION MANAGEMENT; MICROARRAYS; NUCLEAR PROPULSION; ONTOLOGY; PROBABILITY DENSITY FUNCTION; SINGULAR VALUE DECOMPOSITION; THEOREM PROVING; YEAST;

HEURISTIC ALGORITHMS;

SACCHAROMYCES CEREVISIAE;

PROTEOME;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; CLUSTER ANALYSIS; DNA MICROARRAY; GENE EXPRESSION PROFILING; METABOLISM; METHODOLOGY; PHYSIOLOGY; SIGNAL TRANSDUCTION; STATISTICAL ANALYSIS;

ALGORITHMS; CLUSTER ANALYSIS; DATA INTERPRETATION, STATISTICAL; GENE EXPRESSION PROFILING; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PATTERN RECOGNITION, AUTOMATED; PROTEOME; SIGNAL TRANSDUCTION;

EID: 55949097825     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2007.70251     Document Type: Article

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