A novel k-mer mixture logistic regression for methylation susceptibility modeling of CpG dinucleotides in human gene promoters

BMC Bioinformatics

Volumn 13, Issue SUPPL.3, 2012, Pages

  Yang, Youngik ^a   Nephew, Kenneth ^b   Kim, Sun ^c  

^a J CRAIG VENTER INSTITUTE   (United States)

^b Indiana University School of Medicine   (United States)

^c Seoul National University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

CELL TYPES; COMPREHENSIVE MODELING; CPG ISLANDS; CROSS VALIDATION; DIFFERENT RESOLUTIONS; DINUCLEOTIDES; DNA METHYLATION; DNA METHYLATION PATTERN; GENE PROMOTER; GENOMIC SEQUENCE; HUMAN GENES; HYPERMETHYLATION; HYPOMETHYLATION; LOGISTIC REGRESSION MODELS; LOGISTIC REGRESSIONS; LOSS OF ACCURACY; MIXTURE MODEL; NEXT-GENERATION SEQUENCING; PREDICTION ACCURACY; SEQUENCE FEATURES; THREE FOLDS; TISSUE TYPES;

ALKYLATION; CELLS; CYTOLOGY; DISEASES; DNA SEQUENCES; LOGISTICS; METHYLATION; MIXTURES; REGRESSION ANALYSIS;

GENES;

ARTICLE; BIOLOGICAL MODEL; CHROMOSOME 21; CPG ISLAND; DNA METHYLATION; DOWN SYNDROME; GENETICS; HUMAN; NEOPLASM; PROMOTER REGION; STATISTICAL MODEL;

CHROMOSOMES, HUMAN, PAIR 21; CPG ISLANDS; DNA METHYLATION; DOWN SYNDROME; HUMANS; LOGISTIC MODELS; MODELS, GENETIC; NEOPLASMS; PROMOTER REGIONS, GENETIC;

EID: 84874519436     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-13-S3-S15     Document Type: Article

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