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Volumn 9, Issue , 2008, Pages
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Discovering biclusters in gene expression data based on high-dimensional linear geometries
a
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Author keywords
[No Author keywords available]
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Indexed keywords
BICLUSTERING ALGORITHM;
CONVENTIONAL CLUSTERING;
FUNCTIONAL ANNOTATION;
GEOMETRIC INTERPRETATION;
HIGH DIMENSIONAL SPACES;
HIGH-DIMENSIONAL DATA SPACE;
MICROARRAY DATA ANALYSIS;
TISSUE CLASSIFICATION;
CLUSTERING ALGORITHMS;
DATA MINING;
GENE EXPRESSION;
GEOMETRY;
HOUGH TRANSFORMS;
MICROARRAYS;
SET THEORY;
MATRIX ALGEBRA;
ALGORITHM;
ARTICLE;
CONTROLLED STUDY;
DNA MICROARRAY;
GENE CLUSTER;
GENE EXPRESSION;
GENE IDENTIFICATION;
HUMAN;
LYMPHOMA;
MICROARRAY ANALYSIS;
NUCLEOTIDE SEQUENCE;
STATISTICAL MODEL;
TUMOR GENE;
AUTOMATED PATTERN RECOGNITION;
BIOLOGY;
CLUSTER ANALYSIS;
DECISION THEORY;
GENE EXPRESSION PROFILING;
GENETICS;
INFORMATION RETRIEVAL;
METHODOLOGY;
STATISTICAL ANALYSIS;
STATISTICS;
ALGORITHMS;
CLUSTER ANALYSIS;
COMPUTATIONAL BIOLOGY;
DATA INTERPRETATION, STATISTICAL;
DECISION THEORY;
GENE EXPRESSION;
GENE EXPRESSION PROFILING;
HUMANS;
INFORMATION STORAGE AND RETRIEVAL;
LINEAR MODELS;
LYMPHOMA;
OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS;
PATTERN RECOGNITION, AUTOMATED;
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EID: 43849109594
PISSN: None
EISSN: 14712105
Source Type: Journal
DOI: 10.1186/1471-2105-9-209 Document Type: Article |
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Times cited : (83)
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References (34)
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