Michael Beer is a Professor of Biomedical Engineering and Genetic Medicine at Johns Hopkins University, affiliated with the McKusick-Nathans Institute of Genetic Medicine and the Department of Biomedical Engineering. His research focuses on computational regulatory genomics, leveraging AI/ML to decode DNA sequence-based gene regulation and its role in development and disease. He holds a PhD from Princeton University and has received awards including the Searle Scholars Award and the Simon Ramo Award. Education: PhD in Astrophysical Sciences, Princeton University, 1995 MA in Astrophysical Sciences, Princeton University, 1991 BSE in Engineering, University of Michigan, 1989 Research Interests: Beer's lab develops computational models to understand enhancer activity, CRISPR-based perturbation, and gene regulatory networks in cancer and disease. They use functional genomics data (ATAC-seq, ChIP-seq, Hi-C) to study regulatory mutations and therapeutic strategies. Key Contributions: Pioneered methods like gkm-SVM for regulatory variant prediction and led ENCODE Consortium efforts. His work bridges machine learning and genomics to model dynamic regulatory networks. Awards: Simon Ramo Award (Thesis in Plasma Physics) DOE Fusion Energy Postdoctoral Fellowship National Science Foundation Graduate Fellowship Searle Scholars Award Johns Hopkins Teaching Excellence Award Lab & Collaborations: Located in the McKusick-Nathans Institute, the lab collaborates with the Ph.D. program in Human Genetics and Genomics. Recent projects include CRISPRi screens and ENCODE grant-funded research on regulatory elements.










