A powerful statistical method for identifying differentially methylated markers in complex diseases

Pacific Symposium on Biocomputing

Volumn , Issue , 2013, Pages 69-79

  Ahn, Surin ^a   Wang, Tao ^a  

^a ALBERT EINSTEIN COLLEGE OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALKYLATION; HISTOLOGY; METHYLATION; REGRESSION ANALYSIS; STATISTICAL TESTS; TISSUE;

ANALYTIC APPROACH; COMPLEX DISEASE; DISEASE PHENOTYPES; EPIGENETIC MODIFICATION; GENERALIZED REGRESSION; IMPORTANT FEATURES; OVARIAN CANCERS; STATISTICAL EFFICIENCY;

DISEASES;

DNA; GENETIC MARKER;

ANALYSIS OF VARIANCE; ARTICLE; BIOLOGY; CASE CONTROL STUDY; COMPUTER SIMULATION; DISEASES; DNA METHYLATION; FEMALE; GENETIC MARKER; GENETIC PROCEDURES; GENETICS; HUMAN; MIDDLE AGED; NUCLEIC ACID DATABASE; OVARY TUMOR; REGRESSION ANALYSIS;

ANALYSIS OF VARIANCE; CASE-CONTROL STUDIES; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DATABASES, NUCLEIC ACID; DISEASE; DNA METHYLATION; DNA, NEOPLASM; FEMALE; GENETIC MARKERS; GENETIC TECHNIQUES; HUMANS; MIDDLE AGED; OVARIAN NEOPLASMS; REGRESSION ANALYSIS;

EID: 84891422343     PISSN: 23356928     EISSN: 23356936     Source Type: Journal    
DOI: None     Document Type: Conference Paper

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