Jun Li, Ph.D.

Jun Li, Ph.D.

Professor of Computational Medicine and Bioinformatics
Associate Chair for Research, Department of Computational Medicine and Bioinformatics
Professor of Human Genetics
734-615-5754

Administrative Contact

Amy Koger
atooze@med.umich.edu
734-764-7330

Areas of Interest

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, which aims to build a strong computational infrastructure to support the rigorous use of single-cell genomic data.  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.  

Main Funding Sources

NIH 1R01DK099034: Genotype-Phenotype relationships underlying aerobic capacity and metabolic health (contact PI: Li, MPIs: Burant, Britton)               

NIH 1R01GM118928: High-resolution map of human germline mutation patterns and inference of mutagenic mechanisms (contact PI: Li, MPI: Zoellner)

NIH R01HL141399: The Molecular Genetics of Venous Thromboembolic Disease (PI, Desch, Co-I: Li)

NIH U01DA043098: Genetics of novelty seeking and propensity for drug abuse in outbred rats (contact PI: Akil, MPI: Li)

NIH 1U24DK112342: Michigan MoTrPAC Chemical Analysis Site (MiCAS) (contact PI: Burant, MPI: Li)

Michigan Institute for Data Science (MIDAS): Michigan Center for Single-Cell Genomic Data Analytics (Co-PI: Li, Gilbert, Co-I: 8 others)

Michigan Diabetes Research Ctr. Study Grant: Elucidating the landscape of liver cell heterogeneity in normal and insulin resistant states by single cell RNA sequencing (co-PI: Lin, Li, Kurabayashi)

Cancer Center Research Committee Innovation Grant: Identifying the cellular source of relapse in AML (Co-PI: Malek, Li)

Taubman Institute Grand Challenge Phase I Grants: Individualized Disease Prediction Using a Multi-Dimensional, Time-Resolved “Big Data” Approach (Co-PI: Choi, Tewari, Co-I, Li)

Pritzker Neuropsychiatric Disorders Research Consortium: Genetic and genomic analyses of psychiatric disorders (PI of subcontract: Li)

NIH 1R01HL139672: Genetic and Genomic Analysis of Arterial Dysplasia (PI: Ganesh, Co-I, Li)

NIH R21HD090371: Comprehensive mapping of mouse testis cell types and spermatogenic stages by single-cell RNA sequencing (PI: Hammoud, Co-I, Li)

Positions Available

The Li lab is recruiting talented individuals with background in quantitative analysis or interest in statistical genetics, bioinformatics, or cancer genomics. Positions are open at multiple levels: graduate student, postdoc, research staff, or research-track faculty. Current projects (2016-2020) include: single-cell RNAseq data analysis, methodological and theoretical research in clustering, mutation patterns in the human genome, multi-omics data integration involving metabolomic, proteomic, and transcriptomic data, QTL mapping in rat models of metabolomic traits and emotional traits. Please contact junzli@med.umich.edu.

Published Articles via Michigan Experts or PubMed

Web Sites