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Pharmacogenomics Volume 15, 2014 - Issue 2
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Research Article

Genome-Wide Association and Pharmacological Profiling of 29 Anticancer Agents Using Lymphoblastoid Cell Lines

Chad C Brown1 Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, NC27607, USAView further author information
,
Tammy M Havener2 Institute for Pharmacogenomics & Individualized Therapy, University of North Carolina at Chapel Hill, Chapel Hill, NC27599, USAView further author information
,
Marisa W Medina3 Children‘s Hospital Oakland Research Institute, Oakland, CA94609, USAView further author information
,
John R Jack1 Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, NC27607, USAView further author information
,
Ronald M Krauss3 Children‘s Hospital Oakland Research Institute, Oakland, CA94609, USAView further author information
,
Howard L McLeod2 Institute for Pharmacogenomics & Individualized Therapy, University of North Carolina at Chapel Hill, Chapel Hill, NC27599, USAView further author information
&
Alison A Motsinger-Reif2 Institute for Pharmacogenomics & Individualized Therapy, University of North Carolina at Chapel Hill, Chapel Hill, NC27599, USA;1 Bioinformatics Research Center, Department of Statistics, North Carolina State University, Raleigh, NC27607, USACorrespondence[email protected]
View further author information
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Pages 137-146 | Received 13 Aug 2013, Accepted 16 Oct 2013, Published online: 21 Jan 2014

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Adrian J Green, Benedict Anchang, Farida S Akhtari, David M Reif & Alison Motsinger-Reif. (2021) Extending the Lymphoblastoid Cell Line Model for Drug Combination Pharmacogenomics. Pharmacogenomics 22:9, pages 543-551.
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John Jack, Tammy M Havener, Howard L McLeod, Alison A Motsinger-Reif & Matthew Foster. (2015) Evaluating the Role of Admixture in Cancer Therapy Via in Vitro Drug Response and Multivariate Genome-Wide Associations. Pharmacogenomics 16:13, pages 1451-1463.
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Nifang Niu & Liewei Wang. (2015) In Vitro Human Cell Line Models to Predict Clinical Response to Anticancer Drugs. Pharmacogenomics 16:3, pages 273-285.
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