Neo Christopher Chung

Neo Christopher Chung

Overview
Modern biotechnologies collect an ever-increasing amount of data about model organisms and humans. To facilitate data-driven discoveries in genomics and medicine, I develop and apply statistical methods for large-scale experimental and observational studies. Particularly, I have extensive experience in analyzing high-dimensional gene expression, genotype, and clinical data to identify underlying signatures of disease status, population structure, and environmental factors. My methodological research focuses on estimating and utilizing systematic patterns of variation, while incorporates resampling strategies and empirical Bayes approaches.

Appointments
Assistant Professor, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw
Visiting Professor, NIH BD2K Center of Excellence for Big Data Computing, University of California, Los Angeles

Education
Fogarty Global Health Fellow [adviser Ben Chi], Centre for Infectious Disease Research in Zambia & UNC-Chapel Hill
Ph.D. in Quantitative and Computational Biology [adviser John Storey], Princeton University
B.S.E. in Biomedical Engineering, Duke University

Publications
NC Chung (2018). Statistical significance of cluster membership with applications to high-throughput genomic data. Biorxiv Pre-print
HJ Painter, NC Chung, A Sebastian, I Albert, JD Storey, M Llinás (2018). Real-time in vivo global transcriptional dynamics during Plasmodium falciparum blood-stage development. Biorxiv Pre-print
NC Chung, C Bolton-Moore, R Chilengi, MP Kasaro, JSA Stringer, BH Chi (2017). Patient engagement in HIV care and treatment in Zambia, 2004–2014. Tropical Medicine & International Health
NC Chung, J Szyda, M Frąszczak, 1000 Bull Genomes Project (2017). Population structure analysis of bull genomes of european and western ancestry. Scientific Reports
NC Chung, JD Storey (2015). Statistical significance of variables driving systematic variation in high-dimensional data. Bioinformatics
J Kim, N Ghasemzadeh, DJ Eapen, NC Chung, JD Storey, AA Quyyumi, G Gibson (2014). Gene expression profiles associated with acute myocardial infarction and risk of cardiovascular death. Genome Medicine