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Modeling cell population dynamics

  • Stony Brook University
  • University of Alberta

Research output: Contribution to journalArticlepeer-review

65 Scopus citations

Abstract

Quantitative modeling is quickly becoming an integral part of biology, due to the ability of mathematical models and computer simulations to generate insights and predict the behavior of living systems. Single-cell models can be incapable or misleading for inferring population dynamics, as they do not consider the interactions between cells via metabolites or physical contact, nor do they consider competition for limited resources such as nutrients or space. Here we examine methods that are commonly used to model and simulate cell populations. First, we cover simple models where analytic solutions are available, and then move on to more complex scenarios where computational methods are required. Overall, we present a summary of mathematical models used to describe cell population dynamics, which may aid future model development and highlights the importance of population modeling in biology.

Original languageEnglish
Pages (from-to)21-39
Number of pages19
JournalIn Silico Biology
Volume13
Issue number1-2
DOIs
StatePublished - 2019

Keywords

  • Mathematical modeling
  • cell population dynamics
  • evolution
  • multiscale simulation algorithms

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