A general strategy to determine the congruence between a hierarchical and a non-hierarchical classification

BMC Bioinformatics

Volumn 8, Issue , 2007, Pages

  Marco, Antonio ^a   Marín, Ignacio ^b  

^a UNIVERSITY OF VALENCIA   (Spain)

^b INSTITUTO DE BIOMEDICINA DE VALENCIA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL NETWORKS; CLASSIFICATION PROCEDURE; EXPRESSION PROFILE; HIERARCHICAL REPRESENTATION; HIERARCHICAL TREE; MITOCHONDRIAL PROTEIN; PERMUTATION ANALYSIS; PHYLOGENETIC INFERENCE;

COMPLEX NETWORKS; INFERENCE ENGINES;

CLASSIFICATION (OF INFORMATION);

MITOCHONDRIAL PROTEIN; SACCHAROMYCES CEREVISIAE PROTEIN;

ARTICLE; CLASSIFICATION ALGORITHM; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENETIC ANALYSIS; NONHUMAN; PHYLOGENY; SACCHAROMYCES CEREVISIAE; SENSITIVITY ANALYSIS; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CLASSIFICATION; CLUSTER ANALYSIS; COMPUTER INTERFACE; DECISION TREE; METABOLISM; METHODOLOGY; PROTEIN ANALYSIS; PROTEIN DATABASE; REPRODUCIBILITY; SEQUENCE ANALYSIS;

ARTIFICIAL INTELLIGENCE; CLASSIFICATION; CLUSTER ANALYSIS; DATABASES, PROTEIN; DECISION TREES; MITOCHONDRIAL PROTEINS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PATTERN RECOGNITION, AUTOMATED; PROTEIN INTERACTION MAPPING; REPRODUCIBILITY OF RESULTS; SACCHAROMYCES CEREVISIAE PROTEINS; SEQUENCE ANALYSIS, PROTEIN; USER-COMPUTER INTERFACE;

EID: 38649130153     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-8-442     Document Type: Article

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