Stochastic modeling for population dynamics: simulation and inference - Part 3 | Vidéo | Carmin.tv

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

By Benoîte de Saporta

Appears in collection : Thematic Month Week 1: PDE and Probability for Biology / Mois thématique Semaine 1 : EDP et probabilité pour la biologie

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.

Information about the video

Date of recording 04/02/2020
Date of publication 21/02/2020
Institution CIRM
Licence CC BY NC ND
Language English
Audience Researchers
Director(s) Luca Recanzone
Format MP4

Citation data

DOI 10.24350/CIRM.V.19604503
Cite this video de Saporta, Benoîte (04/02/2020). Stochastic modeling for population dynamics: simulation and inference - Part 3. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.19604503
URL https://dx.doi.org/10.24350/CIRM.V.19604503

Domain(s)

Probability

Bibliography

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
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
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
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
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
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
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
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
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
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
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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