Cell-based models: Difference between revisions

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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 [[agent-based model]]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>