Jun Li, Ph.D.
Professor of Human GeneticsProfessor & Associate Chair for Research of Computational Medicine and BioinformaticsFaculty, Center for Statistical Genetics; Comprehensive Cancer CenterMember, Depression Center; Michigan Diabetes Research Center; Michigan Metabolomics & Obesity CenterCo-Director, Michigan Center for Single-Cell Genomic Data Analytics
5940A Buhl1241 E. Catherine St. SPC 5618Ann Arbor, MI 48109-5618junzli@med.umich.edu734-615-5754
Affiliations:
About the Lab
The Li lab studies the genetic and functional basis of complex human diseases using genomic approaches. Currently our NIH-supported projects include the analyses of spontaneous mutation patterns in the human genome (NIGMS R01), multi-omic studies of a genetic rat model of addiction behavior (NIDA U01) and a rat model of metabolic health (NIDDK R01). We are part of the MoTrPAC Consortium (U24 NIH Common Funds) which seeks to discover the molecular transducers of the health benefit of physical exercise. Dr. Li co-directs the Michigan Center for Single-Cell Genomic Data Analytics and the Single-Cell Spatial Analysis Program. An overarching theme in the Li lab is the responsible use of complex data in transparent, reproducible, and community extendable research. We are constantly recruiting talented individuals with background in biostatistics and biomedical data science.
Selected Recent News
2022-04 Xianing has graduated with PhD of Human Genetics. Congratulations!
2022-03 Our joint paper with Sue Hammoud's group has appeared in Dev Cell, and U-M Lab Blog
2022-03 Our work with MIDAS was profiled by U-M articles (1 and 2)
2021-03 Xianing received the prestigious Rackham Predoctoral Fellowship. Congratulations!
2019-12 Dr. Li was elected as a Fellow of American Association for the Advancement of Science
2019-12 End of year party at Jun's house
2018.12 MIDAS single-cell biology winter retreat
2018.10 Coverage of a new paper from our collaboration with the Rosenberg group. (STAT)
2018.10 New York Times coverage of the ideology of human genetic diversity
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