Clustering protein sequences with a novel metric transformed from sequence similarity scores and sequence alignments with neural networks

BMC Bioinformatics

Volumn 6, Issue , 2005, Pages

  Ma, Qicheng ^a   Chirn, Gung Wei ^a   Cai, Richard ^a   Szustakowski, Joseph D ^a   Nirmala, Nanguneri R ^a  

^a NOVARTIS INSTITUTES FOR BIOMEDICAL RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING METHODS; CLUSTERING RESULTS; COMPARATIVE STUDIES; EUKARYOTIC GENOME; FALSE POSITIVE AND FALSE NEGATIVES; PROKARYOTIC GENOMES; SEQUENCE ALIGNMENTS; SEQUENCE SIMILARITY;

GENES; NEURAL NETWORKS;

CLUSTERING ALGORITHMS;

AMINO ACID; PROTEIN;

ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; ARTIFICIAL NEURAL NETWORK; EUKARYOTE; GENE CLUSTER; HUMAN GENOME; MATHEMATICAL COMPUTING; PROKARYOTE; PROTEIN ANALYSIS; PROTEIN DOMAIN; PROTEIN FAMILY; SENSITIVITY AND SPECIFICITY; SEQUENCE ALIGNMENT; SEQUENCE HOMOLOGY; STRUCTURAL BIOINFORMATICS; CLUSTER ANALYSIS; COMPUTER PROGRAM; PROCEDURES; QUALITY CONTROL; RECEIVER OPERATING CHARACTERISTIC; SEQUENCE ANALYSIS; VALIDATION STUDY;

EUKARYOTA; PROKARYOTA;

ALGORITHMS; BENCHMARKING; CLUSTER ANALYSIS; NEURAL NETWORKS (COMPUTER); ROC CURVE; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, PROTEIN; SEQUENCE HOMOLOGY, AMINO ACID; SOFTWARE VALIDATION;

EID: 27644494405     PISSN: 14712105     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-6-242     Document Type: Article

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