Charalampos (Babis) Papachristou, Ph.D.

Charalampos (Babis) Papachristou, Ph.D.

Charalampos (Babis) Papachristou, Ph.D.
Associate Professor/Assessment Coordinator

Charalampos (Babis) Papachristou, Ph.D.

Contact Info
856-256-4500 ext. 53863
Robinson Hall 230D



BS (Mathematics), Aristotle University of Thessaloniki, Greece
PhD (Statistics), The Ohio State University
Postdoctoral (Human Genetics), University of Chicago

Research Expertise:
Statistical Genetics | Biostatistics | Genetic Epidemiology

My research interests are in the areas of statistical genetics, epidemiology, and applications to biological and medical studies. I primarily develops novel methodologies for analyzing data from genetic studies to identify disease susceptibility genes. I am currently involved in variety of projects some of which aim at uncovering factors affecting asthma susceptibility, reducing drug wastage in VA hospitals, building mouse models of response to leukemia treatments, and identifying genetic markers that predict drug response to cancer treatment.

Honors and Awards:
Christian R. and Mary F. Lindback Award for Distinguished Teaching - 2013

Member of:
American Statistical Association (ASA)
International Genetic Epidemiology Society (IGES)

Recent Academic Projects:
Unlocking the Heritability of Methylation in Human DNA via the Use of Pedigree Data

Haplotype-based Tests for Detecting Gene-Environment Interactions

Exploring Factors Affecting Eating Habits of College Students

Identifying Factors Contributing to Benign Brain Tumors (Meningiomas)

Recent Publications:
Fazia T, Pastorino R Foco L, Han L, Abney M, Beecham A, Hadjixenofontos A, Guo H, Gentilini D, Papachristou C, Bitti PP, Ticca A, Berzuini C, McCauley JL, Bernardinelli L (2017) Investigating multiple sclerosis genetic susceptibility on the founder population of east-central Sardinia via association and linkage analysis of immune-related loci. Mult Scler. Epub ahead of print.    

Papachristou C, Ober C, Abney M (2016) A LASSO penalized regression approach for genome-wide association analyses using related individuals: application to the Genetic Analysis Workshop 19 simulated data. BMC Proceedings. 10(Suppl 7):53.   

Papachristou, C (2015) A population based confidence set inference method for SNPs that regulate quantitative phenotypes. In: Ordered Data Analysis, Modeling and Health Research Methods (Springer Proceedings in Mathematics & Statistics Vol. 149) Choudhary P, Nagaraja C, Ng H, ed. pp. 235-244, Cham:Springer.



Spring 2024 - Class Schedule
21894 - STAT 02515-1      APPLIED MULTIVARIATE DATA ANLY      M 2:00-4:45       James 3115
21895 - STAT 02515-2      APPLIED MULTIVARIATE DATA ANLY      M 6:30-9:15      James 3115

Spring 2024 - Office Hours
By appointment at