The precise control of central molecular dogma processes, i.e. the ability to quantitatively manipulate and change gene products, is a catalyser for advancing biomedicine and biotechnology, ultimately enabling the design of highly efficient therapies and engineer microorganisms that can shift us from a fossil to bio-based society. Towards this, we couple computer and biological sciences by bringing state-of-the-art machine learning (ML) into synthetic biology, primarily working on two main directions i) gene regulation for the development of protein expression systems and ii) protein engineering to enhance properties. We use highly applied science as a vehicle to explain fundamental mechanisms, i.e. by developing ML models that are quantitatively predictive of molecular phenomena, we identify mechanistic links underlying these predictions. In this presentation, I will discuss the latest application of AI in synthetic biology, demonstrate our recent developments and discuss the lab's future directions.
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22 April, 2022, 14:00
22 April, 2022, 15:00