Research Assistant Professor, PhD, University of North Carolina, 2009. Daniel Adkins' research focuses on statistical modeling in pharmacogenomics and psychiatric genetics. His current work centers on the analysis of large, highly dimensional biomarker assays (e.g., GWAS, metabolomics) and clinical trial/experimental murine data, using latent variable models including mixed effects models, structural equation models, and mixture models. These methods have recently been applied to investigate the genetic precursors of antipsychotic response among schizophrenia patients, antidepressant response among depression patients and the metabolomic correlates of methamphetamine response in mice.