Dr. Mark Gerstein is the Albert L Williams Professor of Biomedical Informatics and Professor of Molecular Biophysics & Biochemistry, Computer Science, and Statistics & Data Science at Yale University, where he has established himself as a leading figure in biomedical data science. After earning his A.B. in physics from Harvard University in 1989, he completed his doctorate in theoretical chemistry and biophysics at Cambridge University in 1993, followed by postdoctoral research in bioinformatics at Stanford University from 1993 to 1996. He joined Yale's faculty in 1997 as an assistant professor and in 2003 assumed the role of co-director of the Yale Computational Biology and Bioinformatics Program, building one of the most influential research groups in computational genomics. His career trajectory demonstrates a remarkable transition from theoretical chemistry to becoming a central figure in the genomic revolution through computational approaches.
Dr. Gerstein's pioneering research has profoundly shaped biomedical data science, with over 700 publications and an H-index exceeding 200, reflecting his substantial scholarly impact across multiple disciplines. His work spans machine learning applications for genomic analysis, macromolecular simulation techniques, comprehensive human genome annotation, disease genomics, and innovative approaches to genomic privacy protection. As a key contributor to major scientific consortia including ENCODE, modENCODE, 1000 Genomes Project, Brainspan, and DOE Kbase, his methodological frameworks have become foundational to modern genomic research. His highest-impact publications in premier journals such as Science, Nature, and Cell have established new paradigms for interpreting biological data through computational lenses, particularly in understanding how genetic variations influence human disease.
Recognized as a leader in his field, Dr. Gerstein received the ISCB Accomplishments by a Senior Scientist Award in 2023 and was named a Fellow of the International Society for Computational Biology in 2015, joining the ranks of the most influential computational biologists globally. He has mentored numerous doctoral students and postdoctoral researchers who have gone on to establish their own successful research programs, as evidenced by his extensive list of advisees across multiple institutions. His current research focuses on developing sophisticated models for variant impact assessment based on allele-specific binding, with particular attention to transcription-factor binding motifs sensitive to mutation. Looking forward, Dr. Gerstein is addressing critical challenges in biomedical research, emphasizing the importance of managing large-scale private genomic data and leveraging digital sensors to achieve more precise phenotypic characterization, thereby shaping the future trajectory of personalized medicine and genomic data science.
