Identification of putative domain linkers by a neural network - Application to a large sequence database

BMC Bioinformatics

Volumn 7, Issue , 2006, Pages

  Miyazaki, Satoshi ^a,b   Kuroda, Yutaka ^c   Yokoyama, Shigeyuki ^a,b  

^a UNIVERSITY OF TOKYO   (Japan)

^b RIKEN YOKOHAMA INSTITUTE   (Japan)

^c TOKYO UNIVERSITY OF AGRICULTURE AND TECHNOLOGY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

DOMAIN BOUNDARY; DOMAIN LINKERS; LARGE SCALE PROTEINS; LARGE SEQUENCES; PROTEIN DATA BANK; SEQUENCE SIMILARITY; STRUCTURAL DOMAINS; STRUCTURAL GENOMICS;

NEURAL NETWORKS; PROTEINS;

DATABASE SYSTEMS;

POLYPEPTIDE; PROTEIN; PROTEIN BINDING;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; PREDICTION; PROTEIN ANALYSIS; PROTEIN DATA BANK; PROTEIN DOMAIN; SENSITIVITY AND SPECIFICITY; SEQUENCE HOMOLOGY; STRUCTURAL GENOMICS; STRUCTURAL PROTEOMICS; SWISS-PROT; ALGORITHM; AMINO ACID SEQUENCE; AUTOMATED PATTERN RECOGNITION; BINDING SITE; CHEMISTRY; DATA BASE; EVALUATION STUDY; INFORMATION RETRIEVAL; MOLECULAR GENETICS; PROCEDURES; PROTEIN DATABASE; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS;

ALGORITHMS; AMINO ACID SEQUENCE; BINDING SITES; DATABASE MANAGEMENT SYSTEMS; DATABASES, PROTEIN; INFORMATION STORAGE AND RETRIEVAL; MOLECULAR SEQUENCE DATA; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; PROTEIN BINDING; PROTEINS; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, PROTEIN;

EID: 33747099239     PISSN: 14712105     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-7-323     Document Type: Article

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