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The Machine Learning for Integrative Genomics team at Institut Pasteur, headed by Laura Cantini, works at the interface of machine learning and biology, developing innovative machine learning
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mediate binding under physiological conditions. The ultimate goal is to establish a detailed structural framework for understanding pili-driven adhesion, opening avenues for the development of anti-adhesion
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behaviour using computational approaches such as Bayesian program synthesis and inverse reinforcement learning. Investigate the diversity of motor commands that could implement observed behaviours and explore
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