From deciphering underlying genetic factors of diseases to developing cutting-edge genome technology, our scientists are making impactful discoveries everyday.
Strength in Genetics and Genomics Research
The Department of Genetics has traditional strengths in computational biology and genome science, as well as model organism, evolutionary and human genetics. Recent specialties include neurological disorders, cellular bioenergetics, epigenomics, personalized medicine and genome technology development.
We have established leadership in the following flagship NIH genomic medicine themed projects:
- The Human Pangenome Project (NHGRI)
- The Impact of Genetic Variation on Function (NHGRI)
- The Long Life Family Study (NIA)
- Somatic Mosaicism across Human Tissues (NIH Common Fund)
- Multi-Omics for Health and Disease (NHGRI, NCI, NIEHS)
- The BRAIN (The Brain Research through Advancing Innovative Neurotechnologies) Initiative Cell Atlas Network (NIMH)
Within the close-knit research community of Washington University School of Medicine, our scientists are supported by a strong foundation. School of Medicine Facts & Figures
| #2 NIH Funding (2023) | $838.3 Million Research Funding 2022 | 19 Nobel Laureates |
Latest News
WashU Medicine rises to No. 2 in nation in NIH research funding (Links to an external site)
Washington University School of Medicine in St. Louis received in 2023 the second highest amount of funding from the National Institutes of Health (NIH) of all medical schools nationwide. This ranking reflects the school’s commitment to cutting-edge research and positions it as a key player in shaping the future of medicine.
Video: PhD Students Talk about New Research on Transposable Elements and Cancer
In the new paper published in Nature Reviews, “Towards targeting transposable elements for cancer therapy”, graduate students Xuan Qu and Yonghao Liang (Holden) summarized the latest research developments in the field. In this video, they talk about their research focus in Dr. Ting Wang’s lab.
Using Interpretable Deep Learning Tools to Decipher Gene Regulation
In this paper, recently published in PLOS Computational Biology, Dr. Michael White, Associate Professor of Genetics and colleagues used a new AI learning package to model data generated with synthetic regulatory DNA elements to further the understanding of regulatory DNA.