Homology induction: The use of machine learning to improve sequence similarity searches

BMC Bioinformatics

Volumn 3, Issue , 2002, Pages

  Karwath, Andreas ^a   King, Ross D ^a  

^a ABERYSTWYTH UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; AMINO ACID SEQUENCE; ANALYTICAL ERROR; ARTICLE; COMPUTER PROGRAM; CONTROLLED STUDY; INTERMETHOD COMPARISON; LOGIC; MATHEMATICAL COMPUTING; PREDICTION; PROTEIN SECONDARY STRUCTURE; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; SEQUENCE DATABASE; SEQUENCE HOMOLOGY; ANIMAL; ARTIFICIAL INTELLIGENCE; BIOLOGY; COMPARATIVE STUDY; EVALUATION; GENETICS; INTERNET; METHODOLOGY; MOUSE; PREDICTION AND FORECASTING; PROTEIN DATABASE; RICE; SEQUENCE ALIGNMENT;

FUNGAL PROTEIN; VEGETABLE PROTEIN; VIRUS PROTEIN;

ALGORITHMS; ANIMALS; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; FUNGAL PROTEINS; INTERNET; MICE; ORYZA SATIVA; PLANT PROTEINS; PREDICTIVE VALUE OF TESTS; RETROVIRIDAE PROTEINS; SENSITIVITY AND SPECIFICITY; SEQUENCE ALIGNMENT; SEQUENCE HOMOLOGY, AMINO ACID;

EID: 0012293533     PISSN: 14712105     EISSN: None     Source Type: Journal    
DOI: 10.1186/1471-2105-3-11     Document Type: Article

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