Integrative phenotyping framework (iPF): Integrative clustering of multiple omics data identifies novel lung disease subphenotypes

BMC Genomics

Volumn 16, Issue 1, 2015, Pages

  Kim, SungHwan ^b,f   Herazo Maya, Jose D ^a   Kang, Dongwan D ^e   Juan Guardela, Brenda M ^a   Tedrow, John ^c   Martinez, Fernando J ^d   Sciurba, Frank C ^c   Tseng, George C ^b,c   Kaminski, Naftali ^a  

^a YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b UNIVERSITY OF PITTSBURGH GRADUATE SCHOOL OF PUBLIC HEALTH   (United States)

^c UNIVERSITY OF PITTSBURGH   (United States)

^d WEILL CORNELL MEDICAL COLLEGE   (United States)

^e LAWRENCE BERKELEY NATIONAL LABORATORY   (United States)

^f Korea University   (South Korea)

Author keywords

Chronic lung disease; Cluster analysis; Genomics; Integrative clustering

Indexed keywords

MESSENGER RNA; MICRORNA;

ADULT; AGED; ARTICLE; CLINICAL FEATURE; CLUSTER ANALYSIS; DISEASE CLASSIFICATION; FEMALE; GENE CLUSTER; GENE EXPRESSION PROFILING; GENOMICS; HUMAN; IMMUNITY; IMMUNOMODULATION; INTEGRATIVE PHENOTYPING FRAMEWORK; INTERSTITIAL LUNG DISEASE; LUNG DISEASE; MAJOR CLINICAL STUDY; MALE; MATHEMATICAL ANALYSIS; MIDDLE AGED; PHENOTYPE; PROTEIN EXPRESSION; VALIDATION STUDY; ALGORITHM; BIOLOGY; COMPUTER SIMULATION; DISCRIMINANT ANALYSIS; INFORMATION PROCESSING; LUNG DISEASES; METABOLISM; MOLECULAR GENETICS; PROCEDURES; WORKFLOW;

ALGORITHMS; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DATASETS AS TOPIC; DISCRIMINANT ANALYSIS; GENOMICS; HUMANS; LUNG DISEASES; MOLECULAR SEQUENCE ANNOTATION; PHENOTYPE; WORKFLOW;

EID: 84947870697     PISSN: None     EISSN: 14712164     Source Type: Journal    
DOI: 10.1186/s12864-015-2170-4     Document Type: Article

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