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H 1 Stochastic modeling for population dynamics: simulation and inference - Part 3

Auteurs : de Saporta, Benoîte (Auteur de la Conférence)
CIRM (Editeur )

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    Résumé : The aim of this course is to present some examples of stochastic models suitable for population dynamics.
    The first part will introduce a class of continuous time models called piecewise deterministic Markov processes (PDMPs). Their trajectories are deterministic with jumps at random times. They are especially suitable to model phenomena with different time scales: a fast time-sacla corresponding to the deterministic behaviour and a slow time-scale corresponding to the jumps. I'll present different biological systems that can be modelled by PDMPs, explain how they can be simulated.
    The second part will focus on random models for cell division when the whole branching population is taken into account. I'll present two data sets from biological experiments trying to determine whether cell division is symmetric or not. I'll explain how statistic tools can help answer this question.

    Keywords : Markov process; numeric probabilities; stochastic control; applications to biology

    Codes MSC :
    60Jxx - Markov processes
    90Cxx - Mathematical programming, See also {49Mxx, 65Kxx}
    92Bxx - Mathematical biology in general

      Informations sur la Vidéo

      Réalisateur : Recanzone, Luca
      Langue : Anglais
      Date de publication : 21/02/2020
      Date de captation : 04/02/2020
      Collection : Research talks ; Probability and Statistics
      Format : MP4
      Durée : 01:14:33
      Domaine : Probability & Statistics
      Audience : Chercheurs ; Doctorants , Post - Doctorants
      Download : https://videos.cirm-math.fr/2020-02-04_Saporta_Part3.mp4

    Informations sur la rencontre

    Nom de la rencontre : Thematic Month Week 1: PDE and Probability for Biology / Mois thématique Semaine 1 : EDP et probabilité pour la biologie
    Organisateurs de la rencontre : Chapuisat, Guillemette ; Cloez, Bertrand ; Henderson, Christopher ; Hubert, Florence ; Pudlo, Pierre ; Raoul, Gaël
    Dates : 05/02/2020 - 09/02/2020
    Année de la rencontre : 2020
    URL Congrès : https://conferences.cirm-math.fr/2301.html

    Citation Data

    DOI : 10.24350/CIRM.V.19604503
    Cite this video as: de Saporta, Benoîte (2020). Stochastic modeling for population dynamics: simulation and inference - Part 3. CIRM. Audiovisual resource. doi:10.24350/CIRM.V.19604503
    URI : http://dx.doi.org/10.24350/CIRM.V.19604503


    Voir aussi

    Bibliographie

    1. COWAN, Richard et STAUDTE, Robert. The bifurcating autoregression model in cell lineage studies. Biometrics, 1986, p. 769-783. - http://dx.doi.org/10.2307/2530692

    2. STEWART, Eric J., MADDEN, Richard, PAUL, Gregory, et al. Aging and death in an organism that reproduces by morphologically symmetric division. PLoS biology, 2005, vol. 3, no 2. - https://doi.org/10.1371/journal.pbio.0030045

    3. GUYON, Julien, et al. Limit theorems for bifurcating Markov chains. Application to the detection of cellular aging. The Annals of Applied Probability, 2007, vol. 17, no 5/6, p. 1538-1569. - https://arxiv.org/abs/0710.5434

    4. GÉGOUT-PETIT, Anne, DE SAPORTA, Benoîte, et BERCU, Bernard. Asymptotic Analysis for Bifurcating Autoregressive Processes via a martingale approach. - https://arxiv.org/abs/0807.0528

    5. DELMAS, Jean-François et MARSALLE, Laurence. Detection of cellular aging in a Galton–Watson process. Stochastic Processes and their Applications, 2010, vol. 120, no 12, p. 2495-2519. - https://dx.doi.org/10.1016/j.spa.2010.07.002

    6. DE SAPORTA, Benoîte, GÉGOUT-PETIT, Anne, MARSALLE, Laurence, et al. Parameters estimation for asymmetric bifurcating autoregressive processes with missing data. Electronic Journal of Statistics, 2011, vol. 5, p. 1313-1353. - https://dx.doi.org/10.1214/11-EJS643

    7. WANG, Ping, ROBERT, Lydia, PELLETIER, James, et al. Robust growth of Escherichia coli. Current biology, 2010, vol. 20, no 12, p. 1099-1103. - https://doi.org/10.1016/j.cub.2010.04.045

    8. DE SAPORTA, Benoîte, GÉGOUT-PETIT, Anne, et MARSALLE, Laurence. Asymmetry tests for bifurcating auto-regressive processes with missing data. Statistics & Probability Letters, 2012, vol. 82, no 7, p. 1439-1444. - https://arxiv.org/abs/1112.3745

    9. DE SAPORTA, Benoîte, GÉGOUT-PETIT, Anne, et MARSALLE, Laurence. Random coefficients bifurcating autoregressive processes. ESAIM: Probability and Statistics, 2014, vol. 18, p. 365-399. - https://arxiv.org/abs/1205.3658

    10. DE SAPORTA, Benoíte, GÉGOUT-PETIT, Anne, et MARSALLE, Laurence. Statistical study of asymmetry in cell lineage data. Computational Statistics & Data Analysis, 2014, vol. 69, p. 15-39. - https://dx.doi.org/10.1016/j.csda.2013.07.025

    11. DELYON, Bernard, DE SAPORTA, Benoîte, KRELL, Nathalie, et al. Investigation of asymmetry in E. coli growth rate. arXiv preprint arXiv:1509.05226, 2015. - https://arxiv.org/abs/1509.05226

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