Michael Beer, a professor in biomedical engineering, focuses on understanding how gene regulatory information is encoded in genomic DNA sequence and how regulatory variation contributes to diseases. His lab develops machine-learning techniques in which computer algorithms detect regulatory sequences in intergenic DNA. He is a member of the Data Science and AI Institute and holds secondary appointments in Genetic Medicine, Oncology, and Molecular Biology and Genetics.
Beer received his undergraduate degree from the University of Michigan in 1989. He earned his MA and PhD from Princeton University in 1991 and 1995, respectively. He joined Johns Hopkins in 2005.
Prior to joining Johns Hopkins, he was the Lewis Thomas Postdoctoral Fellow in the Department of Molecular Biology and Lewis-Sigler Institute for Integrative Genomics at Princeton University.
Beer was recognized with the Simon Ramo Award for his thesis in plasma physics. He also was awarded the DOE Fusion Energy Postdoctoral Fellowship and the National Science Foundation Graduate Fellowship, and the Searle Scholars Award for promising junior facility.
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Discovery could enable the development of therapies for cancer or other genomic diseases by activating genes on demand.