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Chen Hua

Professor
Beijing Institute of Genomics
Chinese Academy of Sciences
China

Biography

Dr. CHEN Hua is a professor and principal investigator of the Population Genetics and Computational Genomics Group at Beijing Institute of Genomics (BIG), Chinese Academy of Sciences (CAS). Dr. Chen received the B.S. and M.S. degrees in Genetics from Fudan University, Shanghai, China in 2001. He received a Ph.D. in Integrative Biology (with emphasis in Computational Genomic Biology) from University of California, Berkeley, USA in December 2007 (advisor: Dr. Montgomery Slatkin). Dr. Chen did postdoctoral research in Harvard Medical School and School of Public Health, and the Broad Institute. He was a research assistant professor in Temple University, USA before joining BIG. Dr. Chen’s expertise is theoretical population genetics. His recent work includes coalescent theory for the joint allele frequency spectrum, the asymptotic coalescent distributions and statistical methods for detecting natural selection (hidden Markov model, XP-CLR etc).

Research Interest

The Population Genetics and Computational Genomics Group (PGCG) has two research focuses: one goal is to develop computationally efficient statistical methods for analyzing genomic data. We also apply these methods in analyzing large scale genomic data from humans and various species, to address interesting biological questions, such as, the mechanism of evolutionary process; the evolutionary history of humans and other species; the genetic architecture of complex traits etc.

Publications

  • Chen H*. (2015). Population genetic studies in the genomic sequencing era. Zoological Research. 36(1): 1-11.

  • Chen H.*, Hey J., and Slatkin M. (2015). A hidden Markov model for investigating recent positive selection. Theoretical Population Biology. 99:18-30.

  • Chen H*, Hey J, Chen K. (2015). Inferring Very Recent Population Growth Rate from Population-Scale Sequencing Data: Using a Large-Sample Coalescent Estimator. Molecular Biology and Evolution. 32(11):2996-3011.

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