A Machine Learning Approach for Identifying Amino Acid Signatures in the HIV Env Gene Predictive of Dementia

PLoS ONE

Volumn 7, Issue 11, 2012, Pages

  Holman, Alexander G ^a   Gabuzda, Dana ^a,b  

^a DANA FARBER CANCER INSTITUTE   (United States)

^b HARVARD MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID; ANTIRETROVIRUS AGENT;

ACCURACY; AMINO ACID ANALYSIS; ARTICLE; CEREBROSPINAL FLUID ANALYSIS; CLASSIFIER; COHORT ANALYSIS; CONTROLLED STUDY; DECISION TREE; FISHER EXACT TEST; HIV ASSOCIATED DEMENTIA; HIV ENV GENE; HUMAN; HYDROPHOBICITY; LEARNING ALGORITHM; MACHINE LEARNING; MAJOR CLINICAL STUDY; NONHUMAN; NUCLEOTIDE SEQUENCE; PREDICTION; SEQUENCE ANALYSIS; VALIDATION STUDY; VIRAL GENETICS; VIRUS GENE;

AIDS DEMENTIA COMPLEX; ALGORITHMS; AMINO ACID MOTIFS; ARTIFICIAL INTELLIGENCE; BRAIN; COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; ENV GENE PRODUCTS, HUMAN IMMUNODEFICIENCY VIRUS; HIV-1; HUMANS; PHYLOGENY; REPRODUCIBILITY OF RESULTS;

EID: 84869103380     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0049538     Document Type: Article

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