Faculty Profile

Sebastian  Zöllner, PhD

Sebastian Zöllner, PhD

  • Professor, Biostatistics Department
  • Professor, Psychiatry Department
  • 4627 SPH I Tower
  • 1415 Washington Heights
  • Ann Arbor, Michigan 48109-2029
  • Language(s) Spoken:
    • German

Sebastian Zöllner is a Professor of Biostatistics. He also holds an appointment in the Department of Psychiatry. Dr. Zöllner joined the University of Michigan after a postdoctoral fellowship in the Department of Human Genetics at the University of Chicago. His research effort is divided between generating new methods in statistical genetics and analyzing data. The general thrust of his work is problems from human genetics, evolutionary biology and statistical population biology.

  • PhD, Biology, University of Munich, 2001
  • M.S., Mathematics, University of Munich, 1997

  • Population Genetics: Human genome variation provides intriguing insights into the evolution of our species and into the biology of heritable traits. My research focuses on developing methods for modeling the stochastic processes generating this variation. Based on these models I make inferences about human population history and develop tools for mapping disease variants.

    Copy number variation: Copy number variants (CNVs) are segments of the genome that exist in different copy numbers in the population. As CNVs encompass genes as well as non-coding DNA, they are good candidates for functional variation. I have design methods for competitive genome hybridization (CGH) data and for hybridization intensities in SNP genotype data.

    Rare Variants: As it is now possible to generate extensive sequence data for large samples, it may be possible to understand the contribution of rare variants to common complex diseases. I am working on several approaches to address statistical challenges related to this new data.

    Genetics of psychiatric diseases: Most psychiatric diseases have high heritability; for example bipolar disorder has a sibling relative risk of 8. Nevertheless, identifying risk variants affecting these diseases has been challenging. I address this challenge by applying modern genetic tools and developing methods to understand the phenotypic heterogeneity of many disorders.

  • American Society of Human Genetics