A Gradual Evolution in Bioinformatics Research

This talk will survey my lab's computational biology research from the 1990s to the present and touch upon the broader directions of the field. I'll start by discussing some early work on structure and simulation and how this transitioned into studying protein and gene networks and, eventually, human genome annotation with machine-learning models. Finally, I'll discuss some of our current work developing models for variant impact based on allele-specific binding and how this highlights the role of transcription-factor binding motifs that are particularly sensitive to mutation. I'll end with thoughts on where I think the field is going. In particular, I’ll discuss the importance of dealing with large amounts of private data and using digital sensors to phenotype individuals more accurately.

Biography

After graduating from Harvard with an AB in physics in 1989, Prof. Mark Gerstein earned a doctorate in theoretical chemistry and biophysics from Cambridge in 1993. He did postdoctoral research at Stanford and then came to Yale in 1997 as an assistant professor. In 2003 he became co-director of the Yale Computational Biology & Bioinformatics Program. Prof. Gerstein has published appreciably, with >600 publications, including several in prominent venues, such as Science and Nature. His research is focused on biomedical data science, and he is particularly interested in machine learning, macromolecular simulation, human-genome annotation, disease genomics, and biomedical privacy.

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