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

BACKGROUND: The increased multi-omics information on carefully phenotyped patients in studies of complex diseases requires novel methods for data integration. Unlike continuous intensity measurements from most omics data sets, phenome data contain clinical variables that are binary, ordinal and cate...

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Gorde:
Xehetasun bibliografikoak
Argitaratua izan da:BMC Genomics
Egile Nagusiak: Kim, SungHwan, Herazo-Maya, Jose D., Kang, Dongwan D., Juan-Guardela, Brenda M., Tedrow, John, Martinez, Fernando J., Sciurba, Frank C., Tseng, George C., Kaminski, Naftali
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: BioMed Central 2015
Gaiak:
Methodology Article
Sarrera elektronikoa:https://ncbi.nlm.nih.gov/pmc/articles/PMC4642618/
https://ncbi.nlm.nih.gov/pubmed/26560100
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12864-015-2170-4
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