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

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

Abstract 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 app...

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Bibliographic Details
Main Authors: Xinyu Zhang, Ying Hu, Bradley E. Aouizerat, Gang Peng, Vincent C. Marconi, Michael J. Corley, Todd Hulgan, Kendall J. Bryant, Hongyu Zhao, John H. Krystal, Amy C. Justice, Ke Xu
Format: Article
Language:English
Published: BMC 2018-12-01
Series:Clinical Epigenetics
Subjects:
DNA methylation
Ensemble machine learning
HIV frailty
Mortality
Tobacco smoking
Online Access:http://link.springer.com/article/10.1186/s13148-018-0591-z

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http://link.springer.com/article/10.1186/s13148-018-0591-z

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