Cell-based models: Difference between revisions

Revision as of 12:07, 10 November 2022

Revision as of 20:36, 15 November 2022

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{{Orphan|date=August 2017}}

'''Cell-based models''' are [[mathematical model]]s that represent biological [[cell (biology)|cells]] as a discrete entities. Within the field of [[computational biology]] they are often simply called [[Agentagent-based model|agent-based models]]s<ref name=":0" /> of which they are a specific application and they are used for simulating the [[biomechanics]] of multicellular structures such as [[Tissue (biology)|tissue]]s. to study the influence of these behaviors on how tissues are organised in time and space. Their main advantage is the easy integration of cell level processes such as [[cell division]], intracellular processes and [[single-cell variability]] within a cell population.<ref name=Liederkerke2015>{{cite journal | vauthors = Van Liedekerke P, Palm MM, Jagiella N, Drasdo D | title=Simulating tissue mechanics with agent-based models: concepts, perspectives and some novel results|journal=Computational Particle Mechanics|date=1 December 2015|volume=2|issue=4|pages=401–444|doi=10.1007/s40571-015-0082-3 | bibcode=2015CPM.....2..401V|doi-access=free}}</ref>

Continuum-based models (PDE-based) models have also been developed – in particular, for cardiomyocytes and neurons. These represent the cells through explicit geometries and take into account spatial distributions of both intracellular and extracellular processes. They capture, depending on the research question and areas, ranges from a few to many thousand cells. In particular, the framework for electrophysiological models of cardiac cells is well-developed and made highly efficient using [[high-performance computing]].<ref>{{cite book | url=https://link.springer.com/book/10.1007/978-3-030-61157-6 | title=Modeling Excitable Tissue | series=Simula SpringerBriefs on Computing |editor=Aslak Tveito |editor2=Kent-Andre Mardal |editor3=Marie E. Rognes | year=2021 | volume=7 | publisher=Springer| doi=10.1007/978-3-030-61157-6 | isbn=978-3-030-61156-9 | s2cid=228872673 }}</ref>

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== Model types ==

Cell-based models can be divided into on- and off-lattice models.

=== On-lattice ===

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Due in part to the increase in computational power, they have arisen as an alternative to [[continuum mechanics]] models<ref>{{cite journal | vauthors = Rodriguez EK, Hoger A, McCulloch AD | title = Stress-dependent finite growth in soft elastic tissues | journal = Journal of Biomechanics | volume = 27 | issue = 4 | pages = 455–467 | date = April 1994 | pmid = 8188726 | doi = 10.1016/0021-9290(94)90021-3 }}</ref> which treat tissues as viscoelastic materials by averaging over single cells.

Cell-based mechanics models are often coupled to models describing intracellular dynamics, such as an [[ordinary differential equation|ODE]] representation of a relevant [[gene regulatory network]]. It is also common to connect them to a [[partial differential equation|PDE]] describing the diffusion of a chemical [[cell signaling|signaling molecule]] through the [[extracellular matrix]], in order to account for [[cellular communication|cell-cell communication]]. As such, cell-based models have been used to study processes ranging from [[embryogenesis]]<ref>{{cite journal | vauthors = Tosenberger A, Gonze D, Bessonnard S, Cohen-Tannoudji M, Chazaud C, Dupont G | title = A multiscale model of early cell lineage specification including cell division | journal = NPJnpj Systems Biology and Applications | volume = 3 | issue = 1 | pages = 16 | date = 9 June 2017 | pmid = 28649443 | pmc = 5466652 | doi = 10.1038/s41540-017-0017-0 }}</ref> over [[Epithelium|epithelial]] [[morphogenesis]]<ref>{{cite journal | vauthors = Fletcher AG, Cooper F, Baker RE | title = Mechanocellular models of epithelial morphogenesis | journal = Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences | volume = 372 | issue = 1720 | pages = 20150519 | date = May 2017 | pmid = 28348253 | pmc = 5379025 | doi = 10.1098/rstb.2015.0519 }}</ref> to tumour growth<ref>{{cite book | vauthors = Drasdo D, Dormann S, Hoehme S, Deutsch A |chapter=Cell-Based Models of Avascular Tumor Growth |veditors=Deutsch A, Howard J, Falcke M, Zimmermann W|title=Function and Regulation of Cellular Systems|date=2004|pages=367–378|doi=10.1007/978-3-0348-7895-1_37|isbn=978-3-0348-9614-6 }}</ref> and intestinal crypt dynamics<ref>{{cite journal | vauthors = De Matteis G, Graudenzi A, Antoniotti M | title = A review of spatial computational models for multi-cellular systems, with regard to intestinal crypts and colorectal cancer development | journal = Journal of Mathematical Biology | volume = 66 | issue = 7 | pages = 1409–1462 | date = June 2013 | pmid = 22565629 | doi = 10.1007/s00285-012-0539-4 | s2cid = 32661526 }}</ref>

== Simulation frameworks ==