The Engineering Biology Forums are a series of talks exploring key tools for the future of engineering biology and biotechnology. Hosted by the Engineering Biology Interdisciplinary Research Centre at the University of Cambridge, the forums will take place Thursdays, 5pm-9pm at the Old Divinity School, St Johns College, Cambridge. Keynote lectures and discussion session will be followed by food, drinks and a fair including demonstrations, exhibitions and information showcasing scientific excellence from around the Cambridge engineering biology community.
Thursday 3rd November 2022
Computing for Biology: Impact of machine learning and artificial intelligence on data analysis and predictive modelling in biology
Keynote Speakers
Prof. David Baker
Protein design using deep learning
University of Washington, USA
Proteins mediate the critical processes of life and beautifully solve the challenges faced during the evolution of modern organisms. Our goal is to design a new generation of proteins that address current-day problems not faced during evolution. In contrast to traditional protein engineering efforts, which have focused on modifying naturally occurring proteins, we design new proteins from scratch to optimally solve the problem at hand. We now use two approaches. First, guided by Anfinsen’s principle that proteins fold to their global free energy minimum, we use the physically based Rosetta method to compute sequences for which the desired target structure has the lowest energy. Second, we use deep learning methods to design sequences predicted to fold to the desired structures. In both cases, following the computation of amino acid sequences predicted to fold into proteins with new structures and functions, we produce synthetic genes encoding these sequences, and characterize them experimentally. In this talk, I will describe recent advances in protein design using both approaches. David Baker is the director of the Institute for Protein Design, a Howard Hughes Medical Institute Investigator, a professor of biochemistry, and an adjunct professor of genome sciences, bioengineering, chemical engineering, computer science, and physics at the University of Washington. His research group is focused on the design of macromolecular structures and functions. He received his Ph.D. in biochemistry with Randy Schekman at the University of California, Berkeley, and did postdoctoral work in biophysics with David Agard at UCSF. Dr. Baker has published over 550 research papers, been granted over 100 patents, and co-founded 17 companies. Over 70 of his mentees have gone on to independent faculty positions. Dr. Baker is a recipient of the Breakthrough Prize in Life Sciences and is a member of the National Academy of Sciences and the American Academy of Arts and Sciences.
Dr. Bianca Dumitrascu
Explainable machine learning for single cell biology
Department of Computer Science and Technology, University of Cambridge, UK
Dr. Dumitrascu studied as an undergraduate at MIT where she earned a B.S. in Mathematics. She then received her PhD in Computational Biology from Princeton University, followed by a membership in the School of Mathematics at the Institute for Advanced Study (IAS). She is now an Early Career Fellow in the Department of Computer Science and Technology and the University of Cambridge. Bianca's work aims to develop statistical and computational methods to characterise the interplay between morphology and genomics in the early development of organisms. Her long term goal is understanding how single cells aggregate temporal and spatial, chemical and physical information to make decisions about their identity, and how these decisions can be altered through optimal perturbations and experimental design. Informed by both experiment and theory, she is interested in interpretable and principled techniques, deep and shallow alike, with roots in hypothesis testing, domain adaptation, representational learning, and active learning.
Fair Demonstrators and Exhibitors
TumourVue
Cambridge Centre for Data Driven Discovery
More TBC
Register on Eventbrite:
Computing for Biology: Engineering Biology Forum 2022 Tickets, Thu 3 Nov 2022 at 17:00 | Eventbrite
