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GAW20: methods and strategies for the new frontiers of epigenetics and pharmacogenomics

Overview of attention for article published in BMC Proceedings, September 2018
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Title
GAW20: methods and strategies for the new frontiers of epigenetics and pharmacogenomics
Published in
BMC Proceedings, September 2018
DOI 10.1186/s12919-018-0113-1
Pubmed ID
Authors

Nathan L. Tintle, David W. Fardo, Mariza de Andrade, Stella Aslibekyan, Julia N. Bailey, Justo Lorenzo Bermejo, Rita M. Cantor, Saurabh Ghosh, Philip Melton, Xuexia Wang, Jean W. MacCluer, Laura Almasy

Abstract

GAW20 provided a platform for developing and evaluating statistical methods to analyze human lipid-related phenotypes, DNA methylation, and single-nucleotide markers in a study involving a pharmaceutical intervention. In this article, we present an overview of the data sets and the contributions analyzing these data. The data, donated by the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) investigators, included data from 188 families (Nā€‰=ā€‰1105) which included genome-wide DNA methylation data before and after a 3-week treatment with fenofibrate, single-nucleotide polymorphisms, metabolic syndrome components before and after treatment, and a variety of covariates. The contributions from individual research groups were extensively discussed prior, during, and after the Workshop in groups based on discussion themes, before being submitted for publication.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 17%
Researcher 2 17%
Student > Bachelor 1 8%
Student > Master 1 8%
Professor 1 8%
Other 2 17%
Unknown 3 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 17%
Medicine and Dentistry 2 17%
Mathematics 1 8%
Pharmacology, Toxicology and Pharmaceutical Science 1 8%
Computer Science 1 8%
Other 1 8%
Unknown 4 33%