Daniel Schrider

Daniel Schrider is an Associate Professor in the Department of Genetics at the University of North Carolina School of Medicine. His research focuses on developing computational tools for analyzing population genetic data to understand evolutionary processes. He leads the Schrider Lab, which explores topics such as the impact of natural selection on genetic diversity, structural variants, and applying machine learning to evolutionary questions. His work spans species including humans, Drosophila melanogaster, and Anopheles mosquitoes.

Research interests include the population genetics of adaptation, genomic structural variants, and leveraging machine learning for more accurate evolutionary inferences. The lab emphasizes interdisciplinary approaches, combining computational methods with experimental data to address fundamental questions in evolutionary biology and genomics.

Recent publications highlight advancements in detecting introgressed alleles, analyzing kidney transplant failure genetics, and refining genotype imputation methods. Dr. Schrider is affiliated with the Bioinformatics and Computational Biology program and actively contributes to community-driven genomic tools like stdpopsim.