Cell population balance and hybrid modeling of population dynamics for a single gene with feedback

Stamatakis, Michail

doi:10.1016/j.compchemeng.2013.02.006

Cited by 5 publications

(5 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To consider intracellular processes, SCM and PBM should be linked. In this case application of model reduction techniques to the SCM can help keeping the model mathematically tractable . Most of the times one internal coordinate, for example, cell mass, can describe the population with acceptable accuracy.…”

Section: Bioreactor Integrated Modelssupporting

confidence: 78%

Review of the important challenges and opportunities related to modeling of mammalian cell bioreactors

2016

View full text Add to dashboard Cite

Industrialization of mammalian cell culture has been achieved by integrating knowledge from several applying core concepts of chemical engineering, cellular and molecular biology, and biochemistry. Modeling has been applied to biological and physical processes to gain additional insights into such processes. This article covers modeling of the bioreactor and metabolic processes as it applies to bioprocess. Hydrodynamics of a bioreactor is briefly described while additional focus is given to gas‐liquid mass transfer. Biological modeling is presented in the order of increasing complexity. First steady state models are presented followed by dynamic models, cybernetic models, and finally bioreactor integrated models. The closing discussion summarizes challenges of implementation of model‐based approaches in the biopharmaceutical industry. © 2016 American Institute of Chemical Engineers AIChE J, 63: 398–408, 2017

show abstract

Section: Bioreactor Integrated Modelssupporting

confidence: 78%

Review of the important challenges and opportunities related to modeling of mammalian cell bioreactors

2016

View full text Add to dashboard Cite

show abstract

“…Based on simulated samples of individual cells, density estimation techniques [64] are then used to reconstruct the density function N(t, x). This approach can also be combined with the grid-based method in the so-called hybrid simulation methods [65,66].…”

Section: Illustrates How the Cellular Dynamics And Cell Division Influence The Dynamics Of The Number Density Function N(t X)mentioning

confidence: 99%

Estimation methods for heterogeneous cell population models in systems biology

Waldherr¹

2018

J. R. Soc. Interface.

View full text Add to dashboard Cite

Heterogeneity among individual cells is a characteristic and relevant feature of living systems. A range of experimental techniques to investigate this heterogeneity is available, and multiple modelling frameworks have been developed to describe and simulate the dynamics of heterogeneous populations. Measurement data are used to adjust computational models, which results in parameter and state estimation problems. Methods to solve these estimation problems need to take the specific properties of data and models into account. The aim of this review is to give an overview on the state of the art in estimation methods for heterogeneous cell population data and models. The focus is on models based on the population balance equation, but stochastic and individual-based models are also discussed. It starts with a brief discussion of common experimental approaches and types of measurement data that can be obtained in this context. The second part describes computational modelling frameworks for heterogeneous populations and the types of estimation problems occurring for these models. The third part starts with a discussion of observability and identifiability properties, after which the computational methods to solve the various estimation problems are described.

show abstract

“…In order to quantify the heterogeneity and combine it with the pertinent genetic network, we introduce the CPB models, which were developed in mid 1960s (Eakman et al, 1966;Fredrickson et al, 1967;Tsuchiya et al, 1966). They are partial integrodifferential equations and are characterized from high mathematical complexity -even with the application of model-reduction techniques (Stamatakis, 2013). Analytical solutions cannot be obtained for the general case and the use of numerical methods is mandatory, as presented in numerous studies (Liou et al, 1997;Mantzaris et al, 2001aMantzaris et al, , 2001bMantzaris et al, , 2001cZhang et al, 2003;Zhang et al, 2002;Zhu et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

Effect of cell heterogeneity on isogenic populations with the synthetic genetic toggle switch network: Bifurcation analysis of two-dimensional cell population balance models

Chrysinas

Kavousanakis

Boudouvis

2018

Computers & Chemical Engineering

View full text Add to dashboard Cite

The dynamics of gene regulatory networks are often modeled with the assumption of cellular homogeneity. However, this assumption contradicts the plethora of experimental results in a variety of systems, which designates that cell populations are heterogeneous systems in the sense that properties such as size, shape, and DNA/RNA content are unevenly distributed amongst their individuals. In order to address the implications of heterogeneity, we utilize the so-called cell population balance (CPB) models. Here, we solve numerically multivariable CPB models to study the effect of heterogeneity on populations carrying the toggle switch network, which features nonlinear behavior at the single-cell level. In order to answer whether this nonlinear behavior is inherited to the heterogeneous population level, we perform bifurcation analysis on the steady-state solutions of the CPB model. We show that bistability is present at the population level with the pertinent bistability region shrinking when the impact of heterogeneity is enhanced.

show abstract

Cell population balance and hybrid modeling of population dynamics for a single gene with feedback

Cited by 5 publications

References 41 publications

Review of the important challenges and opportunities related to modeling of mammalian cell bioreactors

Review of the important challenges and opportunities related to modeling of mammalian cell bioreactors

Estimation methods for heterogeneous cell population models in systems biology

Effect of cell heterogeneity on isogenic populations with the synthetic genetic toggle switch network: Bifurcation analysis of two-dimensional cell population balance models

Contact Info

Product

Resources

About