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UID:0-902@lptms.universite-paris-saclay.fr
DTSTART;TZID=Europe/Paris:20230915T110000
DTEND;TZID=Europe/Paris:20230915T120000
DTSTAMP:20230911T124400Z
URL:http://www.lptms.universite-paris-saclay.fr/seminars/physics-biology-i
 nterface-seminar-quantifying-uncertainty-in-symmetric-particle-based-model
 s-for-statistical-inference/
SUMMARY:Physics-Biology Interface seminar: Quantifying Uncertainty in Symme
 tric Particle-Based Models for Statistical Inference - Salle des séminair
 es du FAST et du LPTMS\, bâtiment Pascal n°530 - 15 Sep 23 11:00
DESCRIPTION:Quantifying Uncertainty in Symmetric Particle-Based Models for 
 Statistical Inference\n\nAntonin Della Noce (Institut Gustave Roussy)\n\nA
 bstract: Particle-based or Individual-Based Models (IBMs)\, initially deve
 loped for kinetic gas theory\, have found applications across various scie
 ntific disciplines\, including computational biology\, for the purpose of 
 explaining emergent macroscopic phenomena from microscopic interactions. I
 n many applications\, some parameters of the system need to be inferred fr
 om observation data carrying very partial information on the underlying po
 pulation / particle assembly This presentation is divided in two parts. Th
 e initial part addresses the issue of parameter inference in scenarios whe
 re observational data provide limited information about the underlying pop
 ulation or particle assembly. It will discuss the propagation of this part
 ial system knowledge into uncertainties associated with parameter values. 
 The subsequent part focuses on the evaluation of the consistency of mean-f
 ield approximations\, specifically within the framework of a model represe
 nting plant populations in competition for light\, which is partially obse
 rved.\n\n\nBio: Antonin Della Noce obtained his Ph.D. in Applied Mathemati
 cs from the Laboratory of Mathematics and Computer Science for Complex Sys
 tems (MICS) at Université Paris-Saclay. His doctoral research focused on 
 population dynamical systems. Following his Ph.D.\, Antonin collaborated w
 ith Institut Gustave Roussy to conduct biostatistical research aimed at pr
 edicting breast cancer toxicities through the use of high-throughput prote
 omics. Additionally\, he worked with Hôpital Bichat on developing screeni
 ng strategies for sequencing patients suspected of having connective tissu
 e disorders.
CATEGORIES:physbio,seminars
LOCATION:Salle des séminaires du FAST et du LPTMS\, bâtiment Pascal n°53
 0\, rue André Riviere\, Orsay\, 91405\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=rue André Riviere\, Orsay\
 , 91405\, France;X-APPLE-RADIUS=100;X-TITLE=Salle des séminaires du FAST 
 et du LPTMS\, bâtiment Pascal n°530:geo:0,0
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TZID:Europe/Paris
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DTSTART:20230326T030000
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