Hierarchical learning architecture with automatic feature selection for multiclass protein fold classification

IEEE Transactions on Nanobioscience

Volumn 2, Issue 4, 2003, Pages 221-232

  Huang, Chuen Der ^a,b   Lin, Chin Teng ^a   Pal, Nikhil Ranjan ^c  

^a NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

^b HSIUPING INSTITUTE OF TECHNOLOGY   (Taiwan)

^c INDIAN STATISTICAL INSTITUTE   (India)

Author keywords

Feature extraction; Gating network; N gram coding; Protein sequence; Radial basis function network (RBFN); Structure Classification of Protein (SCOP); Support vector machine (SVM)

Indexed keywords

AMINO ACIDS; COMPUTATIONAL METHODS; DATA ACQUISITION; FEATURE EXTRACTION; GATEWAYS (COMPUTER NETWORKS); INFORMATION RETRIEVAL; NEURAL NETWORKS; PROBLEM SOLVING; PROTEINS; RADIAL BASIS FUNCTION NETWORKS;

GATING NETWORK; N-GRAM CODING; PROTEIN SEQUENCE; STRUCTURE CLASSIFICATION OF PROTEIN (SCOP); SUPPORT VECTOR MACHINE (SVM);

HIERARCHICAL SYSTEMS;

GOES;

PROTEIN;

ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; CHEMISTRY; CLASSIFICATION; CLUSTER ANALYSIS; COMPARATIVE STUDY; COMPUTER ANALYSIS; EVALUATION; METHODOLOGY; MOLECULAR GENETICS; PROTEIN CONFORMATION; PROTEIN FOLDING; REPRODUCIBILITY; ROBOTICS; SENSITIVITY AND SPECIFICITY; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS; SEQUENCE HOMOLOGY; VALIDATION STUDY;

ALGORITHMS; AMINO ACID SEQUENCE; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTING METHODOLOGIES; MOLECULAR SEQUENCE DATA; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; PROTEIN CONFORMATION; PROTEIN FOLDING; PROTEINS; REPRODUCIBILITY OF RESULTS; ROBOTICS; SENSITIVITY AND SPECIFICITY; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, PROTEIN; SEQUENCE HOMOLOGY, AMINO ACID;

EID: 3042810113     PISSN: 15361241     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNB.2003.820284     Document Type: Article

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