Improving the prediction of clinical outcomes from genomic data using multiresolution analysis

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 9, Issue 5, 2012, Pages 1442-1450

  Hennings Yeomans, Pablo H ^a   Cooper, Gregory F ^a  

^a UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE   (United States)

Author keywords

clinical outcomes; genomics; Human genome; multiresolution; pattern recognition; prediction; single nucleotide polymorphisms; SNPs; wavelets

Indexed keywords

CLINICAL OUTCOME; GENOMICS; HUMAN GENOMES; MULTI-RESOLUTIONS; SINGLE NUCLEOTIDE POLYMORPHISMS; SNPS; WAVELETS;

FORECASTING; LOGISTICS; PATTERN RECOGNITION; REGRESSION ANALYSIS; SIGNAL PROCESSING;

GENES;

ALZHEIMER DISEASE; ARTICLE; GENETIC ASSOCIATION; GENETIC DATABASE; GENETICS; GENOMICS; METHODOLOGY; STATISTICAL MODEL;

ALZHEIMER DISEASE; DATABASES, GENETIC; GENOME-WIDE ASSOCIATION STUDY; GENOMICS; LOGISTIC MODELS;

EID: 84864922525     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2012.80     Document Type: Article

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