Hierarchical kernel mixture models for the prediction of AIDS disease progression using HIV structural gp120 profiles

BMC Genomics

Volumn 11, Issue SUPPL. 4, 2010, Pages

  Yoo, Paul D ^a,b   Shwen Ho, Yung ^c   Ng, Jason ^d   Charleston, Michael ^a   Saksena, Nitin K ^c   Yang, Pengyi ^e   Zomaya, Albert Y ^a  

^a UNIVERSITY OF SYDNEY   (Australia)

^b KHALIFA UNIVERSITY   (United Arab Emirates)

^c WESTMEAD HOSPITAL   (Australia)

^d Etisalat BT Innovation Centre (EBTIC)   (United Arab Emirates)

^e CSIRO   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

GLYCOPROTEIN GP 120;

ACCURACY; ACQUIRED IMMUNE DEFICIENCY SYNDROME; ANALYTICAL ERROR; ARTICLE; BIOINFORMATICS; CLINICAL ASSESSMENT; CONTROLLED STUDY; DISEASE COURSE; HUMAN IMMUNODEFICIENCY VIRUS; KERNEL METHOD; MACHINE LEARNING; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; NUCLEOTIDE SEQUENCE; PATHOGENESIS; PREDICTION; PROTEIN GLYCOSYLATION; PROTEIN STRUCTURE; QUALITY CONTROL; SUPPORT VECTOR MACHINE; ARTIFICIAL INTELLIGENCE; BIOLOGICAL MODEL; BIOLOGY; COHORT ANALYSIS; COMPARATIVE STUDY; COMPUTER PROGRAM; GENETICS; GLYCOSYLATION; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS INFECTION; METABOLISM; PREDICTIVE VALUE;

AIDS DISEASE; BIOINFORMATICS TOOLS; CLINICAL ASSESSMENTS; DATA SETS; DISEASE PROGRESSION; MACHINE-LEARNING; MIXTURE MODEL; PREDICTIVE PERFORMANCE; STRUCTURAL FRAMEWORKS; STRUCTURAL PROFILES; TARGET SEQUENCES; VIRAL PATHOGENESIS;

BENCHMARKING; CARBOHYDRATES; ESTERIFICATION; FORECASTING; GLYCOSYLATION; LEARNING SYSTEMS;

BIOINFORMATICS;

ACQUIRED IMMUNODEFICIENCY SYNDROME; ARTIFICIAL INTELLIGENCE; BENCHMARKING; COHORT STUDIES; COMPUTATIONAL BIOLOGY; DISEASE PROGRESSION; GLYCOSYLATION; HIV ENVELOPE PROTEIN GP120; HIV SEROPOSITIVITY; HUMANS; MODELS, BIOLOGICAL; PREDICTIVE VALUE OF TESTS; SOFTWARE;

EID: 78649778477     PISSN: None     EISSN: 14712164     Source Type: Journal    
DOI: 10.1186/1471-2164-11-S4-S22     Document Type: Article

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