Wikipedia

Cell-based models: Difference between revisions

Browse history interactively
← Previous edit
Content deleted Content added
VisualWikitext
m →Simulation frameworks: activated table property: sortable
OAbot (talk | contribs)
Bots
646,409 edits
m Open access bot: doi updated in citation with #oabot.
 
(36 intermediate revisions by 17 users not shown)
Line 1:
{{Short description|Mathematical models representing biological cells}}
'''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>▼
{{Orphan|date=August 2017}}
 
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>▼
▲'''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 [[Agent-based model|agent-based models]]<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 |editor=Aslak Tveito |editor2=Kent-Andre Mardal |editor3=Marie E. Rognes | year=2021 | publisher=Springer}}</ref>
 
== Model types ==
 
Cell-based models can be divided into on- and off-lattice models.
 
=== On-lattice ===
On-lattice models such as [[Cellular automaton|cellular automata]] or [[Cellular Potts model|cellular potts]] restrict the spatial arrangement of the cells to a fixed grid. The mechanical interactions are then carried out according to literature-based rules (cellular automata)<ref>{{cite journal | vauthors = Peirce SM, Van Gieson EJ, Skalak TC | title = Multicellular simulation predicts microvascular patterning and in silico tissue assembly | journal = FASEB Journal | volume = 18 | issue = 6 | pages = 731–3731–733 | date = April 2004 | pmid = 14766791 | doi = 10.1096/fj.03-0933fje | s2ciddoi-access = 11107214free | urls2cid = http://www.fasebj.org/content/18/6/731.short11107214 }}</ref> or by minimizing the total energy of the system (cellular potts),<ref>{{cite journal | vauthors = Graner F, Glazier JA | title = Simulation of biological cell sorting using a two-dimensional extended Potts model | journal = Physical Review Letters | volume = 69 | issue = 13 | pages = 2013–2016 | date = September 1992 | pmid = 10046374 | doi = 10.1103/PhysRevLett.69.2013 | bibcode = 1992PhRvL..69.2013G }}</ref> resulting in cells being displaced from one grid point to another.
 
=== Off-lattice ===
 
Off-lattice models allow for continuous movement of cells in space and evolve the system in time according to [[force]] laws governing the mechanical interactions between the individual cells. Examples of off-lattice models are center-based models,<ref>{{cite journal | vauthors = Osborne JM, Fletcher AG, Pitt-Francis JM, Maini PK, Gavaghan DJ | title = Comparing individual-based approaches to modelling the self-organization of multicellular tissues | journal = PLOS Computational Biology | volume = 13 | issue = 2 | pages = e1005387 | date = February 2017 | pmid = 28192427 | pmc = 5330541 | doi = 10.1371/journal.pcbi.1005387 | veditors = Nie Q | bibcode = 2017PLSCB..13E5387O | veditorsdoi-access = Nie Qfree }}</ref> vertex-based models,<ref name=":0" /> models
based on the [[immersed boundary method]]<ref>{{cite journal | vauthors = Rejniak KA | title = An immersed boundary framework for modelling the growth of individual cells: an application to the early tumour development | journal = Journal of Theoretical Biology | volume = 247 | issue = 1 | pages = 186–204 | date = July 2007 | pmid = 17416390 | doi = 10.1016/j.jtbi.2007.02.019 | bibcode = 2007JThBi.247..186R }}</ref> and the subcellular element
method.<ref>{{cite book | vauthors = Newman TJ | title = Single-Cell-Based Models in Biology and Medicine | chapter = Modeling multicellularMulticellular Structures Using systemsthe usingSubcellular subcellularElement elementsModel | journal = Mathematical Biosciences and Engineering | volume = 2 | issue = 3 | pages = 613–24 | date = July 2005 | pmid = 20369943 | doi = 10.1007/978-3-7643-8123-3_10 | series = Mathematics and Biosciences in Interaction | isbn = 978-3-7643-8101-1 }}</ref> They differ mainly in the level of detail with which they represent the
cell shape. As a consequence they vary in their ability to capture different biological mechanisms, the effort needed to extend them from two- to three-dimensional models and also in their computational cost.<ref>{{cite journal | vauthors = Osborne JM, Fletcher AG, Pitt-Francis JM, Maini PK, Gavaghan DJ | title = Comparing individual-based approaches to modelling the self-organization of multicellular tissues | journal = PLOS Computational Biology | volume = 13 | issue = 2 | pages = e1005387 | date = February 2017 | pmid = 28192427 | pmc = 5330541 | doi = 10.1371/journal.pcbi.1005387 | bibcode = 2017PLSCB..13E5387O | doi-access = free }}</ref>
 
The simplest off-lattice model, the center-based model, depicts cells as spheres and models their mechanical interactions using pairwise potentials.<ref>{{cite journal | vauthors = Meineke FA, Potten CS, Loeffler M | title = Cell migration and organization in the intestinal crypt using a lattice-free model | journal = Cell Proliferation | volume = 34 | issue = 4 | pages = 253–66253–266 | date = August 2001 | pmid = 11529883 | pmc = 6495866 | doi = 10.1046/j.0960-7722.2001.00216.x | pmc = 6495866 }}</ref><ref>{{cite journal | vauthors = Drasdo D, Höhme S | title = A single-cell-based model of tumor growth in vitro: monolayers and spheroids | journal = Physical Biology | volume = 2 | issue = 3 | pages = 133–47133–147 | date = July 2005 | pmid = 16224119 | doi = 10.1088/1478-3975/2/3/001 | bibcode = 2005PhBio...2..133D | s2cid = 24191020 }}</ref> It is easily extended to a large number of cells in both 2D and 3D.<ref>{{cite journal | vauthors = Galle J, Aust G, Schaller G, Beyer T, Drasdo D | title = Individual cell-based models of the spatial-temporal organization of multicellular systems--achievements and limitations | journal = Cytometry. Part A | volume = 69 | issue = 7 | pages = 704–10704–710 | date = July 2006 | pmid = 16807896 | doi = 10.1002/cyto.a.20287 | doi-access = free }}</ref>
 
==== Vertex ====
Line 29 ⟶ 27:
 
Since they account for individual behavior at the cell level such as [[cell proliferation]], [[cell migration]] or [[apoptosis]], cell-based models are a useful tool to study the influence of these behaviors on how tissues are organised in time and space.<ref name=Liederkerke2015 />
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 = 455–67455–467 | 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 ==
Line 46 ⟶ 44:
!Speedup
|-
|ACAM<ref>{{cite journal | vauthors = Nestor-Bergmann A, Blanchard GB, Hervieux N, Fletcher AG, Étienne J, Sanson B | title = Adhesion-regulated junction slippage controls cell intercalation dynamics in an Apposed-Cortex Adhesion Model | journal = PLOS Computational Biology | volume = 18 | issue = 1 | pages = e1009812 | date = January 2022 | pmid = 35089922 | doi = 10.1371/journal.pcbi.1009812 | pmc = 8887740 | s2cid = 246387965 | doi-access = free | bibcode = 2022PLSCB..18E9812N }}</ref>
|Agents.jl<ref>{{Cite journal |last=Datseris |first=George |last2=Vahdati |first2=Ali R. |last3=DuBois |first3=Timothy C. |date=2022-01-05 |title=Agents.jl: a performant and feature-full agent-based modeling software of minimal code complexity |url=http://journals.sagepub.com/doi/10.1177/00375497211068820 |journal=SIMULATION |language=en |pages=003754972110688 |doi=10.1177/00375497211068820 |issn=0037-5497}}</ref>▼
|Off-lattice, ODE solvers
|2D
|<ref>{{cite journal | vauthors = Nestor-Bergmann A, Blanchard GB, Hervieux N, Fletcher AG, Étienne J, Sanson B | title = ACAM - Apposed Cortex Adhesion Model | year = 2021 | doi = 10.1101/2021.04.11.439313
| s2cid = 233246026 | url = https://zenodo.org/record/5838249 | via = Zenodo | doi-access = free }}</ref>
|Yes
|Yes
|[[Python (programming language)|Python]]
|
|-
▲|Agents.jl<ref>{{Cite journal |last vauthors = Datseris |first=GeorgeG, |last2=Vahdati |first2=AliAR, R. |last3=DuBois |first3=Timothy C.TC |date=2022-01-05 |title=Agents.jl: a performant and feature-full agent-based modeling software of minimal code complexity |url=http://journals.sagepub.com/doi/10.1177/00375497211068820 |journal=SIMULATIONSimulation |language=en |pages=003754972110688 |doi=10.1177/00375497211068820 |arxiv=2101.10072 |s2cid=231698977 |issn=0037-5497}}</ref>
|Center/agent-based
|2D,3D
|https://github.com/<ref>{{cite web | title = JuliaDynamics/Agents.jl
| url = https://github.com/JuliaDynamics/Agents.jl | via = GitHub }}</ref>
|Yes
|Yes
Line 55 ⟶ 64:
|[https://docs.julialang.org/en/v1/stdlib/Distributed/ Distributed.jl]
|-
|Artistoo<ref>{{Cite journal |last1=Wortel |first1=Inge MN |last2=Textor |first2=Johannes |date=2021-04-09 |editor-last=Walczak |editor-first=Aleksandra M |editor2-last=Buttenschoen |editor2-first=Andreas |editor3-last=Macklin |editor3-first=Paul |title=Artistoo, a library to build, share, and explore simulations of cells and tissues in the web browser |journal=eLife |volume=10 |pages=e61288 |doi=10.7554/eLife.61288 |issn=2050-084X |pmc=8143789 |pmid=33835022 |doi-access=free }}</ref>
|Biocellion<ref>{{cite journal |vauthors=Kang S, Kahan S, McDermott J, Flann N, Shmulevich I |date=November 2014 |title=Biocellion: accelerating computer simulation of multicellular biological system models |journal=Bioinformatics |volume=30 |issue=21 |pages=3101–3108 |doi=10.1093/bioinformatics/btu498 |pmc=4609016 |pmid=25064572}}</ref><ref>{{Cite web |title=biocellion |url=https://biocellion.com/ |access-date=2022-04-05 |website=biocellion |language=en-US}}</ref>▼
|Cellular Potts, Cellular Automaton
|2D, (3D)
|https://github.com/somathiasingewortel/cbmosartistoo▼
|Yes
|Yes
|[[JavaScript]]
|
|-
▲|Biocellion<ref>{{cite journal | vauthors = Kang S, Kahan S, McDermott J, Flann N, Shmulevich I |date=November 2014title |title= Biocellion: accelerating computer simulation of multicellular biological system models | journal = Bioinformatics | volume = 30 | issue = 21 | pages = 3101–3108 | date = November 2014 | pmid = 25064572 | pmc = 4609016 | doi = 10.1093/bioinformatics/btu498 |pmc=4609016 |pmid=25064572}}</ref><ref>{{Cite web |title=biocellion |url=https://biocellion.com/ |access-date=2022-04-05 |website=biocellion |language=en-US}}</ref>
|Center/agent-based
|
Line 64 ⟶ 82:
|
|-
| cellular_raza
|CBMOS<ref>{{Cite journal |last=Mathias |first=Sonja |last2=Coulier |first2=Adrien |last3=Hellander |first3=Andreas |date=2022-01-31 |title=CBMOS: a GPU-enabled Python framework for the numerical study of center-based models |url=https://doi.org/10.1186/s12859-022-04575-4 |journal=BMC Bioinformatics |volume=23 |issue=1 |pages=55 |doi=10.1186/s12859-022-04575-4 |issn=1471-2105 |pmc=PMC8805507 |pmid=35100968}}</ref>▼
|Off-lattice, Allows for Generic Implementations
| 1D, 2D, 3D
| [https://github.com/jonaspleyer/cellular_raza github.com/jonaspleyer/cellular_raza]
| Yes
| [https://docs.rs/cellular_raza Yes]
| [[Rust_(programming_language)|Rust]]
|
|-
▲|CBMOS<ref>{{Citecite journal |last vauthors = Mathias |first=SonjaS, |last2=Coulier |first2=AdrienA, |last3=Hellander |first3=AndreasA |date=2022-01-31 |title = CBMOS: a GPU-enabled Python framework for the numerical study of center-based models |url=https://doi.org/10.1186/s12859-022-04575-4 |journal = BMC Bioinformatics | volume = 23 | issue = 1 | pages = 55 | date = January 2022 | pmid = 35100968 | pmc = 8805507 | doi = 10.1186/s12859-022-04575-4 |issn=1471 doi-2105access |pmc=PMC8805507 |pmid=35100968free }}</ref>
|Center/agent-based
|
|<ref>{{cite web | title = JuliaDynamics
▲|https://github.com/somathias/cbmos
| url = https://github.com/somathias/cbmos | via = GitHub }}</ref>
|
|
Line 73 ⟶ 101:
|GPU
|-
|CellularPotts.jl
|Chaste<ref>{{cite journal |vauthors=Pitt-Francis J, Bernabeu MO, Cooper J, Garny A, Momtahan L, Osborne J, Pathmanathan P, Rodriguez B, Whiteley JP, Gavaghan DJ |date=September 2008 |title=Chaste: using agile programming techniques to develop computational biology software |url=http://eprints.maths.ox.ac.uk/846 |journal=Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences |volume=366 |issue=1878 |pages=3111–36 |doi=10.1016/j.cpc.2009.07.019 |pmid=18565813 |archive-url=https://web.archive.org/web/20151120234903/http://eprints.maths.ox.ac.uk/846/ |archive-date=2015-11-20 |access-date=2019-02-01 |author16-link=Sarah L. Waters}}</ref><ref>{{cite journal |vauthors=Mirams GR, Arthurs CJ, Bernabeu MO, Bordas R, Cooper J, Corrias A, Davit Y, Dunn SJ, Fletcher AG, Harvey DG, Marsh ME, Osborne JM, Pathmanathan P, Pitt-Francis J, Southern J, Zemzemi N, Gavaghan DJ |date=14 March 2013 |title=Chaste: an open source C++ library for computational physiology and biology |journal=PLOS Computational Biology |volume=9 |issue=3 |pages=e1002970 |bibcode=2013PLSCB...9E2970M |doi=10.1371/journal.pcbi.1002970 |pmc=3597547 |pmid=23516352}}</ref>▼
|Cellular Potts, agent-based
|2D,3D
|https://github.com/RobertGregg/CellularPotts.jl
|
|not ready for usage
|[[Julia (programming language)|Julia]]
|
|-
▲|Chaste<ref>{{cite journal | vauthors = Pitt-Francis J, Bernabeu MO, Cooper J, Garny A, Momtahan L, Osborne J, Pathmanathan P, Rodriguez B, Whiteley JP, Gavaghan DJ |date display-authors =September 20086 | title = Chaste: using agile programming techniques to develop computational biology software |url=http://eprints.maths.ox.ac.uk/846 |journal = Philosophical Transactions. of the Royal Society of LondonSeries A:, Mathematical, Physical, and Engineering Sciences | volume = 366 | issue = 1878 | pages =3111–36 3111–3136 | date = September 2008 | pmid = 18565813 | doi = 10.1016/j.cpc.2009.07.019 |pmid=18565813 |archive-url = https://web.archive.org/web/20151120234903/http://eprints.mathsora.ox.ac.uk/846objects/ |archiveuuid:61d9bb9f-date=201595c6-114054-208118-294f6ca94d54/files/m680698b55b2efad4aabc9cdd27c24a09 | access-date = 2019-02-01 | author16-link = Sarah L. Waters | archive-url = | archive-date = }}</ref><ref>{{cite journal | vauthors = Mirams GR, Arthurs CJ, Bernabeu MO, Bordas R, Cooper J, Corrias A, Davit Y, Dunn SJ, Fletcher AG, Harvey DG, Marsh ME, Osborne JM, Pathmanathan P, Pitt-Francis J, Southern J, Zemzemi N, Gavaghan DJ |date=14 Marchdisplay-authors 2013= 6 | title = Chaste: an open source C++ library for computational physiology and biology | journal = PLOS Computational Biology | volume = 9 | issue = 3 | pages = e1002970 |bibcode date =2013PLSCB...9E2970M 14 March 2013 | pmid = 23516352 | pmc = 3597547 | doi = 10.1371/journal.pcbi.1002970 |pmc bibcode =3597547 2013PLSCB...9E2970M |pmid doi-access =23516352 free }}</ref>
|Center/agent-based, on-/off-lattice, cellular automata, vertex-based, immersed boundary
|2D, 3D
|[https://github.com/Chaste/Chaste https://github.com/Chaste/Chaste]
|Yes
|Yes
Line 82 ⟶ 119:
|
|-
|[[CompuCell3D]]<ref>{{cite book |title=Computational Methods in Cell Biology |vauthors=Swat MH, Thomas GL, Belmonte JM, Shirinifard A, Hmeljak D, Glazier JA |datetitle=1Computational January 2012 |journal=Methods in Cell Biology |chapter=Multi-Scale Modeling of Tissues Using CompuCell3D |date=1 January 2012 |isbn=9780123884039 |volume=110 |pages=325–66 |chapter=Multi-scale modeling of tissues using CompuCell3D |doi=10.1016/B978-0-12-388403-9.00013-8 |pmc=3612985 |pmid=22482955}}</ref>
|Cellular Potts, PDE solvers, cell type automata
|3D
Line 91 ⟶ 128:
|[[OpenMP]]
|-
|EdgeBased<ref>{{Cite journal |last vauthors = Brown |first=PhillipPJ, J. |last2=Green |first2=J.JE, Edward F. |last3=Binder |first3=BenjaminBJ, J. |last4=Osborne |first4=James M. |date=2021-02-10JM |title=A rigid body framework for multi-cellular modelling |url journal =https://www.biorxiv.org/content/10.1101/ Nature Computational Science | date = November 2021.02.10.430170v1 |language volume =en 1 | issue = 11 | pages =2021.02.10.430170 754–766 |doi=10.1038/s43588-021-00154-4|biorxiv=10.1101/2021.02.10.430170v1.full430170|pmid=38217146 |s2cid=231939320}}</ref>
|Off-lattice, ODE solvers
|2D
Line 100 ⟶ 137:
|
|-
|EPISIM<ref>{{cite journal | vauthors = Sütterlin T, Huber S, Dickhaus H, Grabe N | title = Modeling multi-cellular behavior in epidermal tissue homeostasis via finite state machines in multi-agent systems | journal = Bioinformatics | volume = 25 | issue = 16 | pages = 2057–2063 | date = August 2009 | pmid = 19535533 | doi = 10.1093/bioinformatics/btp361 | doi-access = free }}</ref>
|EPISIM<ref>{{Cite web |url=https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btp361 |access-date=2022-11-08 |website=academic.oup.com |doi=10.1093/bioinformatics/btp361}}</ref>
|Center/agent-based
|2D, 3D
Line 109 ⟶ 146:
|
|-
|IAS (Interacting Active Surfaces)<ref>{{Cite journal |last vauthors = Torres-Sánchez |first=AlejandroA, |last2=Winter |first2=MaxMK, Kerr |last3=Salbreux |first3=GuillaumeG |date=2022-03-22 |title=Interacting active surfaces: a model for three-dimensional cell aggregates |url journal =https://www.biorxiv.org/content/10.1101/2022.03.21.484343v1 bioRxiv |languagevolume=en18 |issue=12 |pages=2022.03.21.484343 |doi=10.1101/2022.03.21.484343|pmid=36525467 |pmc=9803321 |s2cid=247631653 }}</ref>
|[[Finite element method|FEM]], ODE solvers
|3D
Line 127 ⟶ 164:
|
|-
|LBIBCell<ref>{{cite journal | vauthors = Tanaka S, Sichau D, Iber D |date=July 2015 |title = LBIBCell: a cell-based simulation environment for morphogenetic problems | journal = Bioinformatics | volume = 31 | issue = 14 | pages =2340–7 2340–2347 |arxiv date =1503.06726 July 2015 | pmid = 25770313 | doi = 10.1093/bioinformatics/btv147 |pmid arxiv =25770313 1503.06726 | s2cid = 16749503 }}</ref>
|Lattice-Boltzmann, Immersed Boundary
|2D
Line 136 ⟶ 173:
|[[OpenMP]]
|-
|MecaGen<ref>{{cite journal | vauthors = Delile J, Herrmann M, Peyriéras N, Doursat R |date=January 2017title |title= A cell-based computational model of early embryogenesis coupling mechanical behaviour and gene regulation | journal = Nature Communications | volume = 8 | pages = 13929 |bibcode date =2017NatCo...813929D January 2017 | pmid = 28112150 | pmc = 5264012 | doi = 10.1038/ncomms13929 |pmc=5264012 |pmidbibcode =28112150 2017NatCo...813929D }}</ref>
|Center/agent-based
|3D
Line 145 ⟶ 182:
|[[CUDA]], [[Graphics processing unit|GPU]]
|-
|Minimal Cell<ref>{{Citecite journal |last vauthors = Thornburg |first=ZaneZR, R. |last2=Bianchi |first2=DavidDM, M. |last3=Brier |first3=TroyTA, A. |last4=Gilbert |first4=BenjaminBR, R. |last5=Earnest |first5=TylerTM, M. |last6=Melo |first6=MarceloMC, C. R. |last7=Safronova |first7=NataliyaN, |last8=Sáenz |first8=JamesJP, P. |last9=Cook |first9=AndrásAT, T. |last10=Wise |first10=KimKS, S. |last11=Hutchison |first11=ClydeCA, A. |last12=Smith |first12=HamiltonHO, O. |last13=Glass |first13=JohnJI, I. |last14=Luthey-Schulten |first14=ZaidaZ |date=2022-01 display-20authors = 6 | title = Fundamental behaviors emerge from simulations of a living minimal cell |url language =https://www.cell.com/cell/abstract/S0092-8674(21)01488-4 English | journal = Cell |language=English |volume = 185 | issue = 2 | pages = 345–360.e28 | date = January 2022 | pmid = 35063075 | doi = 10.1016/j.cell.2021.12.025 |issn pmc =0092-8674 9985924 |pmid s2cid =35063075 246065847 | doi-access = free }}</ref>
|ODE solvers, stochastic PDE solvers
|3D
Line 154 ⟶ 191:
|[[CUDA]], [[Graphics processing unit|GPU]]
|-
|Morpheus<ref>{{cite journal | vauthors = Starruß J, de Back W, Brusch L, Deutsch A |date=May 2014title |title= Morpheus: a user-friendly modeling environment for multiscale and multicellular systems biology | journal = Bioinformatics | volume = 30 | issue = 9 | pages =1331–2 1331–1332 | date = May 2014 | pmid = 24443380 | pmc = 3998129 | doi = 10.1093/bioinformatics/btt772 |pmc=3998129 |pmid=24443380}}</ref>
|Cellular Potts, ODE solvers, PDE solvers
|2D, 3D
Line 172 ⟶ 209:
|
|-
|PhysiCell<ref>{{cite journal | vauthors = Ghaffarizadeh A, Heiland R, Friedman SH, Mumenthaler SM, Macklin P |date=February 23,title 2018= |title=PhysiCell: anAn Openopen Sourcesource Physicsphysics-Basedbased Cellcell Simulatorsimulator for 3-D Multicellularmulticellular Systemssystems | journal = PLOS Computational Biology | volume = 14 | issue = 2 | pages = e1005991 |bibcode date =2018PLSCB..14E5991G February 2018 | pmid = 29474446 | pmc = 5841829 | doi = 10.1371/journal.pcbi.1005991 |pmc bibcode =5841829 2018PLSCB..14E5991G |pmid doi-access =29474446 free }}</ref>
|Center/agent-based, ODE
|3D
Line 190 ⟶ 227:
|
|-
|Timothy<ref>{{Cite journal |last vauthors = Cytowski |first=MaciejM, |last2=Szymanska |first2=ZuzannaZ |date=September 2014-09 |title=Large-Scale Parallel Simulations of 3D Cell Colony Dynamics |url=https://ieeexplore.ieee.org/document/6728930 |journal=Computing in Science & Engineering |volume=16 |issue=5 |pages=86–95 |doi=10.1109/MCSE.2014.2 |bibcode=2014CSE....16e..86C |s2cid=427712 |issn=1558-366X}}</ref>
|Center/agent-based
|3D
Line 199 ⟶ 236:
|[[Message Passing Interface|MPI]], [[OpenMP]]
|-
|URDME - DLCM workflow<ref>{{cite journal | vauthors = Engblom S, Wilson DB, Baker RE |date=August 2018title |title= Scalable population-level modelling of biological cells incorporating mechanics and kinetics in continuous time | journal = Royal Society Open Science | volume = 5 | issue = 8 | pages = 180379 |arxiv date =1706.03375 August 2018 |bibcode pmid =2018RSOS....580379E 30225024 | pmc = 6124129 | doi = 10.1098/rsos.180379 |pmc bibcode =6124129 2018RSOS....580379E |pmid arxiv =30225024 1706.03375 }}</ref><ref>{{Cite web |title=URDME |url=http://urdme.github.io/urdme/ |access-date=2022-04-05 |website=URDME |language=en-US}}</ref>
|[[Finite element method|FEM]], [[Finite volume method|FVM]]
|2D,3D
Line 208 ⟶ 245:
|
|-
|VirtualLeaf<ref>{{Citationcite book |last vauthors = Antonovici CC, Peerdeman GY, Wolff HB, Merks RM |first title =Claudiu-Cristi Plant Systems Biology |title chapter = Modeling Plant Tissue Development Using VirtualLeaf |date=2022 |url=https://doi.org/10.1007/978-1-0716-1816-5_9series |work=Plant SystemsMethods in Molecular Biology: Methods| andvolume Protocols= 2395 | pages = 165–198 |editor-last=Lucas |editor-first=Mikaëldate |place=New York,2022 NY| pmid |publisher=Springer 34822154 |language=en |doi = 10.1007/978-1-0716-1816-5_9 | publisher = Springer | isbn = 978-1-0716-1816-5 |access-date=2022-11-08 |last2=Peerdeman |first2hdl =Guacimo Y.1887/3479570 |last3=Wolff |first3s2cid =Harold B.244668621 |last4 place =Merks New York, NY |first4 veditors =Roeland Lucas M. H.}}</ref> (2021)
|Off-lattice
|2D
Line 217 ⟶ 254:
|
|-
|yalla<ref>{{Citecite journal |last vauthors = Germann |first=PhilippP, |last2=Marin-Riera |first2=MiquelM, |last3=Sharpe |first3=JamesJ |date=2019-03-27 |title = ya{{!}}{{!}}&#124;&#124;a: GPU-Powered Spheroid Models for Mesenchyme and Epithelium |url language =https://www.cell.com/cell-systems/abstract/S2405-4712(19)30068-7 English | journal = Cell Systems |language=English |volume = 8 | issue = 3 | pages = 261–266.e3 | date = March 2019 | pmid = 30904379 | doi = 10.1016/j.cels.2019.02.007 |issn s2cid =2405 85497718 | doi-4712access = free |pmid hdl =30904379 10230/42284 | hdl-access = free }}</ref>
|Center/agent-based
|3D
Line 235 ⟶ 272:
|
|-
|Tyssue<ref>{{Cite journal |last vauthors = Theis |first=SophieS, |last2=Suzanne |first2=MagaliM, |last3=Gay |first3=GuillaumeG |date=2021-06-07 |title=Tyssue: an epithelium simulation library |url=https://joss.theoj.org/papers/10.21105/joss.02973 |journal=Journal of Open Source Software |language=en |volume=6 |issue=62 |pages=2973 |doi=10.21105/joss.02973 |bibcode=2021JOSS....6.2973T |s2cid=235965728 |issn=2475-9066|doi-access=free }}</ref>
|Vertex-based
|2D, 3D
Line 253 ⟶ 290:
|
|}
 
 
== References ==
Line 259 ⟶ 295:
 
[[Category:Cells]]
[[Category:Simulation software]]
[[Category:Numerical analysis]]
[[Category:Biophysics]]
[[Category:Computational biology]]
[[Category:Tissues (biology)]]
Retrieved from "https://en.wikipedia.org/wiki/Cell-based_models"