Profile

Eric Sobel received his PhD from the UCLA Department of Biomathematics in 1996 (before it was renamed Computational Medicine). He is currently the Vice Chair for Education for the Department of Computational Medicine.

He is a research professor in statistical genetics specializing in gene-mapping algorithms. His research interests include the development and application of Markov chain Monte Carlo [MCMC] techniques to allow statistical analysis particularly of large, complex pedigrees. Recently he has been most involved in several projects extending GWAS analysis tools, especially for the analysis of rare variants, interactions, haplotypes, and family data. Another of his core interests is algorithm optimization, including GPU implementations that allow analysis of very large genetic data sets on any system from standard laptops to cloud-based computational servers.

He is also heavily involved with applying gene-mapping algorithms. This work has the dual benefit of making sure that state-of-the-art algorithms are used in the community and that the needs of the community inform his algorithmic development. His recent gene-mapping application work includes breast cancer, obesity, Williams syndrome, migraine, Down syndrome, schizophrenia, corneal dystrophy, psoriasis, familial dyslipidemia, and congenital lipodystrophy.

He is also deeply interested in the development of the next generation of computational geneticists. He has been integrally involved for 20 years, and currently co-directs, an NIH Training Program in Genomic Analysis and Interpretation. He has taught multiple workshops on computational genetics for any interested geneticists each year for over 25 years at locations worldwide, including annually in Cambridge, UK.