High-performance prediction of functional residues in proteins with machine learning and computed input features

Biopolymers

Volumn 95, Issue 6, 2011, Pages 390-400

  Somarowthu, Srinivas ^a   Yang, Huyuan ^a,b   Hildebrand, David G C ^a,c   Ondrechen, Mary Jo ^a  

^a NORTHEASTERN UNIVERSITY   (United States)

^b BOSTON SCIENTIFIC CORPORATION   (United States)

^c HARVARD UNIVERSITY   (United States)

Author keywords

functional residues; POOL; protein function; THEMATICS

Indexed keywords

3D STRUCTURE; ACTIVE SITE; CATALYTIC RESIDUE; COMBINED METHOD; FUNCTIONAL RESIDUES; GENE PRODUCTS; GENOMICS; GEOMETRIC INFORMATION; HIGH-THROUGHPUT; INPUT FEATURES; MACHINE-LEARNING; NOVEL FOLDS; PHYLOGENETIC INFORMATION; POOL; PROTEIN FUNCTION; SEQUENCE SIMILARITY; STRUCTURAL SIMILARITY; STRUCTURE-BASED; THEMATICS; TITRATION CURVES;

ELECTROSTATICS; FORECASTING; GENES; LAKES; THREE DIMENSIONAL;

PROTEINS;

AREA UNDER THE CURVE; ARTICLE; CONTROLLED STUDY; FALSE POSITIVE RESULT; INTERMETHOD COMPARISON; MACHINE LEARNING; PARTIAL ORDER OPTIMAL LIKELIHOOD; PHYLOGENY; PHYSICAL PERFORMANCE; PREDICTIVE VALUE; PROTEIN ANALYSIS; PROTEIN SYNTHESIS; RESIDUE ANALYSIS; THEORETICAL MICROSCOPIC ANOMALOUS TITRATION CURVE SHAPE; ALGORITHM; ARTIFICIAL INTELLIGENCE; BIOLOGY; CHEMISTRY; CONFORMATION; ENZYME ACTIVE SITE; GENETICS; GENOMICS; METHODOLOGY; MOLECULAR GENETICS; PROTEIN FOLDING; STRUCTURE ACTIVITY RELATION;

AMINO ACID; EXO BETA (1 3) D GALACTANASE; EXO-BETA-(1--3)-D-GALACTANASE; GLYCOSIDASE; PROTEIN;

ALGORITHMS; AMINO ACIDS; ARTIFICIAL INTELLIGENCE; CATALYTIC DOMAIN; COMPUTATIONAL BIOLOGY; GENOMICS; GLYCOSIDE HYDROLASES; MOLECULAR CONFORMATION; MOLECULAR SEQUENCE ANNOTATION; PROTEIN FOLDING; PROTEINS; STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 80051764768     PISSN: 00063525     EISSN: 10970282     Source Type: Journal    
DOI: 10.1002/bip.21589     Document Type: Article

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