ReviewJournal of the Royal Society, Interface2018
Estimation methods for heterogeneous cell population models in systems biology.
Review in Journal of the Royal Society, Interface, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- CLADES: a hybrid NeuralODE-Gillespie approach for unveiling clonal cell fate and differentiation dynamics.Nature communications · 2025Article
- Quantifying biological heterogeneity in nano-engineered particle-cell interaction experiments.Journal of the Royal Society, Interface · 2025Article
- An integrative phenotype-structured partial differential equation model for the population dynamics of epithelial-mesenchymal transition.NPJ systems biology and applications · 2025Article
- Computer-aided design of reversible hybridization chain reaction (CAD-HCR) enables multiplexed single-cell spatial proteomics imaging.Science advances · 2022Article
- Population balance modelling captures host cell protein dynamics in CHO cell cultures.PloS one · 2022Article
- Two-Stage Approaches to Accounting for Patient Heterogeneity in Machine Learning Risk Prediction Models in Oncology.JCO clinical cancer informatics · 2021Article
- Uncertainty propagation for deterministic models of biochemical networks using moment equations and the extended Kalman filter.Journal of the Royal Society, Interface · 2021Article
- Pancreatic Ppy-expressing γ-cells display mixed phenotypic traits and the adaptive plasticity to engage insulin production.Nature communications · 2021Article
- Derivation of stationary distributions of biochemical reaction networks via structure transformation.Communications biology · 2021Article
- Stochastic reaction networks in dynamic compartment populations.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Isolating the sources of heterogeneity in nano-engineered particle-cell interactions.Journal of the Royal Society, Interface · 2020Article
- Maximum Entropy Framework for Predictive Inference of Cell Population Heterogeneity and Responses in Signaling Networks.Cell systems · 2020Article
- Inheritance and variability of kinetic gene expression parameters in microbial cells: modeling and inference from lineage tree data.Bioinformatics (Oxford, England) · 2019Article
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1 author.
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Abstract
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.
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