Abstract: Single-cell genomics technologies have been lauded for their potential to probe biological systems with cell type specificity, and to elucidate cellular differentiation trajectories. However, in the rush to learn biology, some important questions about the nature and extent of information in single-cell genomics data overlooked. I will show that biophysical models of transcriptional dynamics are helpful in understanding what can be gleaned from single-cell genomics experiments.

Bio: Lior Pachter was born in Ramat Gan, Israel, and grew up in Pretoria, South Africa where he attended Pretoria Boys High School. After receiving a B.S. in Mathematics from Caltech in 1994, He left for MIT where he was awarded a PhD in applied mathematics in 1999. He then moved to the University of California at Berkeley where he was a postdoctoral researcher (1999-2001), assistant professor (2001-2005), associate professor (2005-2009), and until 2018 the Raymond and Beverly Sackler professor of computational biology and professor of mathematics and molecular and cellular biology with a joint appointment in comp,,,uter science. Since January 2017 he has been the Bren professor of computational biology at Caltech.

His research interests span the mathematical and biological sciences, and he has authored over 100 research articles in the areas of algorithms, combinatorics, comparative genomics, algebraic statistics, molecular biology and evolution. He has taught a wide range of courses in mathematics, computational biology and genomics. He is a Fellow of the International Society of Computational Biology and has been awarded a National Science Foundation CAREER award, a Sloan Research Fellowship, the Miller Professorship, and a Federal Laboratory Consortium award for the successful technology transfer of widely used sequence alignment software developed in his group.

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