Michael Beer,PHD

Associate Professor of Biomedical Engineering and McKusick-Nathans Institute of Genetic Medicine

Specialization: Computational Regulatory Genomics


Johns Hopkins Whiting School of Engineering

720 Rutland Avenue

MRB 573

Baltimore, MD 21205



Beer Lab

The ultimate goal of our research is to understand how gene regulatory information is encoded in genomic DNA sequence.

Recently, we have made significant progress in understanding how DNA sequence features specify cell-type specific mammalian enhancer activity by using kmer-based SVM machine learning approaches. Our work uses functional genomics DNase-seq, ChIP-seq, RNA-seq, and chromatin state data to computationally identify combinations of transcription factor binding sites which operate to define the activity of cell-type specific enhancers.  Our models are then used to predict the impact of regulatory variation associated with common human disease, and have been validated in a wide range of cell-specific reporter assays.


To advance neuroscience discovery by uniting neuroscience, engineering and computational data science to understand the structure and function of the brain.