Chen's research interests mainly focus on statistical genetics and genomics, including computational methods for analyzing large-scale sequencing data, parametric and semiparametric statistical models for correlated data analysis, rare genetic variant association analysis, meta-analysis, gene-environment interactions, with applications to complex disease genetics. His current research projects include: 1) Computationally efficient statistical association tests to account for population structure and relatedness in large-scale multi-ethnic sequencing studies; 2) Gene-environment and gene-treatment interaction tests for epidemiological and pharmacogenomic studies; and 3) Genetic epidemiological studies on complex heritable human diseases, such as obstructive sleep apnea. In 2015, Chen received an NIH Pathway to Independence Award (K99/R00) from the National Heart, Lung, and Blood Institute. "Precision medicine research involves multi-disciplinary collaboration between bioinformaticians, biostatisticians, epidemiologists and physicians." Chen said, "With the advance of technology, we are generating and collecting huge amount of data every day. I am excited about the development of statistical methods and computational tools that can be applied to big data research. Together, we can better understand, treat and prevent complex diseases and improve human health."
Publications/Creative Works
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