Dr. Gökçen Eraslan
Title: Toward understanding disease gene function with single cell genomics and machine learning
Eraslan lab aims to gain insights on how cells function and cause diseases using modern data science and machine learning techniques. This requires characterization of various types of molecular measurements (e.g. gene expression) from high number of cells with expressive representation learning and predictive models. Two main ingredients described above have been enabled by recent breakthroughs in the fields of machine learning and single-cell genomics. First, recent advances in machine learning enabled new techniques to make sense of high throughput datasets in biology. Second, new experimental techniques in single-cell genomics allowed profiling tens of thousands of cells in a single experiment which paved the way for generation of large-scale datasets. Our research field is a new branch of computational biology at the intersection of machine learning and single-cell genomics.
Gokcen Eraslan, Senior AI Scientist at Genentech/Roche, received his M.S. degree in Computational Biology from Aalto University (Harri Lahdesmaki lab) in Finland and his Ph.D. in Computational Biology from Technical University of Munich (Fabian Theis lab) in Germany. His research focuses on developing methods of statistical and machine learning to solve problems in single-cell genomics and human genetics. He recently started his lab at Genentech AI/ML department in South San Francisco.