Open Research and Contributor Identifier

ORCID - 0000-0003-0273-6217

Department

Epidemiology and Biostatistics

Education

• Michigan State University, Ph.D., 2012

• Peking University, M.S., 2007

• Peking University, B.S., 2003

Background

Dr. Li's research interests are in the field of statistical genetics and genetic epidemiology, with a focus on the development of biostatistical methods and their application to complex human diseases, such as birth defects.

Positions

• Associate Professor, Indiana University at Bloomington, July 2019–Present
• Assistant Professor, Indiana University at Bloomington, August 2015–June 2019
• Assistant Professor, University of Arkansas for Medical Sciences, August 2012–July 2015

Selected Publications

Articles

Lyu C, Huang M, Liu N, Chen Z, Tycko B, Lupo P, Witte JS, Hobbs CA, and Li M. Detecting methylation quantitative trait loci using a methylation random field method. Briefings in Bioinformatics Aug. 2021; bbab323

Li M, Lyu C, Huang M, Do C, Tycko B, Lupo P, MacLeod SL, Randolph CE, Liu N, Witte JS, and Hobbs CA. Mapping methylation quantitative trait loci in cardiac tissues nominates risk loci and biological pathways in congenital heart disease. BMC Genomic Data June 2021; 22(1):20

Huang M, Lyu C, Li X, Qureshi AA, Han J, and Li M. Identifying susceptibility loci for cutaneous squamous cell carcinoma using a fast sequence kernel association test. Frontiers in Genetics May 2021; 12:657499

Lyu C, Webber DM, MacLeod SL, Hobbs CA, and Li M. Gene-by-gene interactions associated with conotrocal heart defects. Molecular Genetics and Genomic Medicine Jan. 2020; 8(1):e1010

Li M, He Z, Tong X, Witte JS, and Lu Q. Detecting rare mutations with heterogeneous effects using a family-based genetic random field method. Genetics Oct. 2018; 210(2):463-476

Li M, Li J, Wei C, Lu Q, Tang X, Erickson SW, Macleod SL, and Hobbs CA. A three-way interaction among maternal and fetal variants contributing to congenital heart defects. Annals of Human Genetics Jan. 2016; 80(1):20-31.

Li M, He Z, Schaid DJ, Cleves MA, Nick TG, and Lu Q. A powerful non-parametric statistical framework for family-based association analyses. Genetics May, 2015; 200(1):69-78.

Li M, Cleves MA, Mallick H, Erickson SW, Tang X, Nick TG, Macleod SL, and Hobbs CA. A genetic association study identifies haplotypes associated with obstructive heart defect. Human Genetics Sep 2014; 133(9):1127-38.

Li M, He Z, Zhang M, Zhan X, Wei C, Elston RC, and Lu Q. A generalized genetic randomfield method for genetic association analysis of sequencing data. Genetic Epidemiology April, 2014; 38(3):242-53

Li M, Erickson SW, Hobbs CA, Li J, Tang X, Nick TG, Macleod SL, and Cleves MA. Detecting maternal-fetal genotype interactions associated with conotruncal heart defects: A haplotype-based analysis with penalized logistic regression. Genetic Epidemiology April 2014; 38(3):198-208.

Li M, Peng R, Wei C, and Lu Q. A u-statistic-based random forest approach for genetic association studies with quantitative traits. Frontiers in Biosciences (Elite Ed.) Jun. 1, 2012; 4:2707-17.

Li M, Ye C, Fu W, Elston RC, and Lu Q. Detecting genetic interactions for quantitative traits with u-statistics. Genetic Epidemiology Sep. 2011;35(6):457-68;doi: 10.1002/gepi.20594.

Li M, Romero R, Fu W, and Cui Y. Mapping haplotype-haplotype interactions with adaptive lasso. BMC Genetics Aug. 27, 2010; 11:79:doi: 10.1186/1471/2156-11-79.