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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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mechanoelectrical feedback, it requires specific tools to uncouple them and to decode the transformation of complex acoustic stimuli by the brain. In the lab, we are developing electrophysiological and imaging
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signatures. We hypothesize that this unique program may represent an ancient state of some skeletal muscles fibres and be required for unique mechanical functions. This project aims to address the following
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co-managed by two deputies: Christian Vestergaard, a theoretical physicist, and François Laurent, an applied mathematician and software engineer. The laboratory’s research is centred on uncovering
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redefinition of behavioral features or pose challenges in their detection. The projects To address these challenges, we propose developing a Bayesian Program Synthesis (BPS) methodology for generating synthetic
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are responsible for blood and immune cell production during development. We will now establish how these transient embryonic progenitors and their progeny respond to prenatal challenges, convey persistent
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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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is mostly used to make the site work as you expect it to. The information does not usually directly identify you, but it can give you a more personalized web experience. Because we respect your right
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is mostly used to make the site work as you expect it to. The information does not usually directly identify you, but it can give you a more personalized web experience. Because we respect your right
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focused on deep-phenotyping of individuals with autism and controls including brain imaging (MRI, fMRI, DTI and EEG) and a battery of cognitive tests. Our group is currently developing new methods