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Article

Machine learning selected smoking-associated DNA methylation signatures that predict HIV prognosis and mortality

1 Dec 2018

Abstract excerpt

BACKGROUND: The effects of tobacco smoking on epigenome-wide methylation signatures in white blood cells (WBCs) collected from persons living with HIV may have important implications for their immune-related outcomes, including frailty and mortality. The application of a machine learning approach to the analysis of CpG methylation in the epigenome enables the selection of phenotypically relevant features from...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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PMID: 30545403
DOI: 10.1186/s13148-018-0591-z

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