Andrzej Mizera: Deep reinforcement learning-based approach towards effective cellular reprogramming

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“Cellular reprogramming, understood as the artificial changing of the type or the phenotypic state of a living cell, has been drawing increasing research attention for its therapeutic potential in treating the most complex diseases characterised by malfunctioning cells. It is believed to ultimately facilitate both the prevention and cure of complex diseases, amongst which neurodegenerative disorders and cancer are presumably the most common. This can be achieved by steering living cells into the ‘healthy’ states.

Unfortunately, finding effective interventions that trigger desired changes in biological cells using solely classical wet-lab experiments is difficult, costly, and requires lengthy time commitments. In this presentation, we will discuss our developments of computational methods for the identification of control strategies for the reprogramming of gene regulatory networks (GRNs) in biological cells and our current new approach based on deep reinforcement learning towards scalable and effective reprogramming of GRNs of realistic sizes.”

Andrzej Mizera is a postdoctoral researcher at IDEAS NCBR and at the Faculty of Mathematics, Informatics, and Mechanics at the Uniwersytet Warszawski. His research interests have been mainly focused on problems in the field of computational systems biology, in particular on predictive computational/mathematical modelling of complex biological systems. His record of publications includes works on the development and application of formal methods for the analysis and control of biological regulatory mechanisms and on complex biological data analysis.