Improved general regression network for protein domain boundary prediction

BMC Bioinformatics

Volumn 9, Issue SUPPL. 1, 2008, Pages

  Yoo, Paul D ^a   Sikder, Abdur R ^b   Zhou, Bing Bing ^a   Zomaya, Albert Y ^a  

^a UNIVERSITY OF SYDNEY   (Australia)

^b MICHIGAN TECHNOLOGICAL UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL REQUIREMENTS; LEARNING-BASED METHODS; MACHINE LEARNING MODELS; MACHINE LEARNING TECHNIQUES; POSITION SPECIFIC SCORING MATRIX; PREDICTIVE PERFORMANCE; SECONDARY STRUCTURES; SOLVENT ACCESSIBILITY;

FORECASTING; LEARNING SYSTEMS; NEURAL NETWORKS; PROTEINS;

BENCHMARKING;

ACCURACY; AMINO ACID SEQUENCE; ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; MACHINE LEARNING; PREDICTION; PROTEIN ANALYSIS; PROTEIN DATABASE; PROTEIN DOMAIN; PROTEIN STRUCTURE; PROTEIN TARGETING; RELIABILITY; SCORING SYSTEM; ALGORITHM; AUTOMATED PATTERN RECOGNITION; CHEMISTRY; METHODOLOGY; MOLECULAR GENETICS; PROTEIN TERTIARY STRUCTURE; REGRESSION ANALYSIS; SEQUENCE ANALYSIS;

PROTEIN;

ALGORITHMS; AMINO ACID SEQUENCE; MOLECULAR SEQUENCE DATA; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; PROTEIN STRUCTURE, TERTIARY; PROTEINS; REGRESSION ANALYSIS; SEQUENCE ANALYSIS, PROTEIN;

EID: 41949117705     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-9-S1-S12     Document Type: Article

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