A machine learning based method for the prediction of G protein-coupled receptor-binding PDZ domain proteins

Molecules and Cells

Volumn 27, Issue 6, 2009, Pages 629-634

  Eo, Hae Seok ^a   Kim, Sungmin ^a   Koo, Hyeyoung ^b   Kim, Won ^a  

^a Seoul National University   (South Korea)

^b Sangji University   (South Korea)

Author keywords

G protein coupled receptor; GPCR interacting protein; Machine learning; PDZ domain; Support vector machine

Indexed keywords

AMINO ACID; G PROTEIN COUPLED RECEPTOR; G PROTEIN COUPLED RECEPTOR INTERACTING PROTEIN; PDZ PROTEIN; TRANSCRIPTION FACTOR; UNCLASSIFIED DRUG;

ACCURACY; ARTICLE; CARBOXY TERMINAL SEQUENCE; CONTROLLED STUDY; CRYSTAL STRUCTURE; CYTOPLASM; DATA ANALYSIS; INTERMETHOD COMPARISON; MACHINE LEARNING; MOLECULAR RECOGNITION; NUCLEOTIDE SEQUENCE; PDZ DOMAIN; PREDICTION; PROTEIN ANALYSIS; PROTEIN ASSEMBLY; PROTEIN BINDING; PROTEIN FUNCTION; PROTEIN PROTEIN INTERACTION; PROTEIN STABILITY; PROTEIN STRUCTURE; PROTEIN TARGETING; PROTEIN TRANSPORT; RECEPTOR BINDING; SENSITIVITY AND SPECIFICITY; SIGNAL TRANSDUCTION; SUPPORT VECTOR MACHINE; VALIDATION PROCESS;

AMINO ACID SEQUENCE; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; MODELS, MOLECULAR; MOLECULAR SEQUENCE DATA; PDZ DOMAINS; PROTEIN BINDING; RECEPTORS, G-PROTEIN-COUPLED;

EID: 67650281206     PISSN: 10168478     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10059-009-0091-2     Document Type: Article

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