2014/05/30 by Coralie Fritsch, Fritsch, Coralie, Jérôme Harmand +3
Biochemistry, Genetics and Molecular Biology · Mathematics · #Evolution and Genetic Dynamics #FOS: Biological sciences #Gene Regulatory Network Analysis #Mathematical Biology Tumor Growth #Populations and Evolution (q-bio.PE) #Quantitative Methods (q-bio.QM) #q-bio.PE #q-bio.QM
paper · pdf · doi:10.48550/arxiv.1405.7963
arXiv admin note: substantial text overlap with arXiv:1308.2411
arxiv created 2014/05/30 · openalex publication_date 2014/05/30 · arxiv updated 2014/06/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Population dynamics and in particular microbial population dynamics, though they are complex but also intrinsically discrete and random, are conventionally represented as deterministic differential equations systems. We propose to revisit this approach by complementing these classic formalisms by stochastic formalisms and to explain the links between these representations in terms of mathematical analysis but also in terms of modeling and numerical simulations. We illustrate this approach on the model of chemostat.