Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies

BMC Bioinformatics

Volumn 11, Issue , 2010, Pages

  David, Maria Pamela C ^a   Concepcion, Gisela P ^a   Padlan, Eduardo A ^a  

^a University of the Philippines Diliman   (Philippines)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID COMPOSITIONS; ARTIFICIAL INTELLIGENCE METHODS; CLASSIFICATION ACCURACY; CLASSIFICATION METHODS; LEAVE-ONE-OUT CROSS VALIDATIONS; NAIVE BAYESIAN CLASSIFIER; PHYSIOLOGICAL CONDITION; POLYPEPTIDE BACKBONES;

AMINO ACIDS; ANTIBODIES; ARTIFICIAL INTELLIGENCE; DATA MINING; DECISION TREES; FORECASTING;

CLASSIFICATION (OF INFORMATION);

AMYLOID; ANTIBODY;

ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CHEMISTRY; IMMUNOLOGY; METHODOLOGY; MOLECULAR GENETICS; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS;

ALGORITHMS; AMINO ACID SEQUENCE; AMYLOID; ANTIBODIES; ARTIFICIAL INTELLIGENCE; MOLECULAR SEQUENCE DATA; PATTERN RECOGNITION, AUTOMATED; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, PROTEIN;

EID: 77949516611     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-79     Document Type: Article

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