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Statut |
Confirmé |
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Série |
BIOPHY-ENS-ESPCI |
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Domaines |
physics.bio-ph |
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Date |
Vendredi 4 Fevrier 2022 |
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Heure |
13:00 |
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Institut |
LPENS |
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Salle |
Remotely on Zoom |
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Nom de l'orateur |
Ronceray |
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Prenom de l'orateur |
Pierre |
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Addresse email de l'orateur |
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Institution de l'orateur |
Turing Centre for Living Systems, Université Aix-Marseille |
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Titre |
What can we learn from the stochastic trajectories of biological systems? |
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Résumé |
Stochastic differential equations are often used to model the dynamics of living
systems, from Brownian motion at the molecular scale to the dynamics of cells and
animals. How does one learn such models from experimental data? This task faces
multiple challenges, from information-theoretical limitations to practical
considerations. I will present a recent and ongoing effort to develop new methods
to reconstruct such stochastic dynamical models from experimental data, with a
focus on robustness and data efficiency. This provides a generic means to quantify
complex behavior and unfold the underlying mechanisms of an apparently erratic
trajectory. |
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Numéro de preprint arXiv |
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Commentaires |
https://us02web.zoom.us/j/82420101680?pwd=OUtkN1RCSkVMNVZXb09yYnVWNG5odz09
Meeting ID: 824 2010 1680
Passcode: 452763 |
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Fichiers attachés |
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