Zhaohui Qin
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Zhaohui S. Qin


Summary

Dr. Qin is currently an Associate Professor in the Department of Biostatistics and Bioinformatics at Rollins School of Public Health, Emory University. He is also a faculty member at the Department of Biomedical Informatics, Emory University School of Medicine. Dr. Qin received his B.S. degree in Probability and Statistics from Peking University in 1994 and Ph.D. degree in Statistics from University of Michigan in 2000. He was a postdoctoral fellow in Dr. Jun Liu’s group in Department of Statistics at Harvard University from 2000 to 2003. He joined the Department of Biostatistics at University of Michigan in 2003. In 2010, he moved to his current position in Emory University. Dr. Qin has more than 15 years of experience in statistical modeling and statistical computing with applications in statistical genetics and genomics. Recently, his research is focused on developing Bayesian model-based methods to analyze data generated from applications of next generation sequencing technologies such as ChIP-seq, RNA-seq and resequencing. Dr. Qin also actively collaborates with biomedical scientists and clinicians on various projects that utilizing next generation sequencing technologies to study cancer genomics. Dr. Qin has published more than 100 peer-reviewed research papers covering statistics, bioinformatics, statistical genetics and computational biology. He has supervised more than 10 graduate students and postdoctoral fellows.

Bioinformatics Genetics Genomics Microbiology Statistics

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Work details

Associate Professor

Emory University
August 2010
Biostatistics and Bioinformatics
I have extensive experience in statistical modeling and computing with applications to statistical genetics and genomics. My recent research is focused on developing Bayesian model-based methods to analyze data generated from applications of next-generation sequencing technologies such as ChIP-seq, RNA-seq, Hi-C, WGBS, resequencing, and on developing software so that the methods can be easily adopted by the research community. I am also actively collaborating with biomedical scientists and clinicians on projects that utilize next-generation sequencing technologies to better understand genomics and epigenomics.


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