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Tytuł:
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Cells in Silico - introducing a high-performance framework for large-scale tissue modeling.
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Autorzy:
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Berghoff M; Steinbuch Centre for Computing, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, 76344, Germany.
Rosenbauer J; John von Neumann Institute for Computing, Jülich Supercomputer Centre, Forschungszentrum Jülich, Jülich, 52428, Germany.
Hoffmann F; Steinbuch Centre for Computing, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, 76344, Germany.
Schug A; John von Neumann Institute for Computing, Jülich Supercomputer Centre, Forschungszentrum Jülich, Jülich, 52428, Germany. .; Faculty of Biology, University of Duisburg-Essen, Essen, 45141, Germany. .
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Źródło:
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BMC bioinformatics [BMC Bioinformatics] 2020 Oct 06; Vol. 21 (1), pp. 436. Date of Electronic Publication: 2020 Oct 06.
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Typ publikacji:
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Journal Article
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Język:
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English
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Imprint Name(s):
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Original Publication: [London] : BioMed Central, 2000-
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MeSH Terms:
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Computer Simulation*
Organ Specificity*
Cells/*metabolism
Biological Transport ; Cell Death ; Diffusion ; Models, Theoretical ; Mutation/genetics ; User-Computer Interface
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References:
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Phys Rev Lett. 1992 Sep 28;69(13):2013-2016. (PMID: 10046374)
Comput Phys Commun. 2007 Jun;176(11-12):670-681. (PMID: 18084624)
Development. 2015 Apr 1;142(7):1203-11. (PMID: 25804733)
J Integr Bioinform. 2020 Apr 7;17(1):. (PMID: 32267247)
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Contributed Indexing:
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Keywords: Cellular Potts model; Massively parallel; Tissue growth
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Entry Date(s):
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Date Created: 20201007 Date Completed: 20201030 Latest Revision: 20201030
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Update Code:
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20240105
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PubMed Central ID:
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PMC7542106
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DOI:
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10.1186/s12859-020-03728-7
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PMID:
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33023471
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Background: Discoveries in cellular dynamics and tissue development constantly reshape our understanding of fundamental biological processes such as embryogenesis, wound-healing, and tumorigenesis. High-quality microscopy data and ever-improving understanding of single-cell effects rapidly accelerate new discoveries. Still, many computational models either describe few cells highly detailed or larger cell ensembles and tissues more coarsely. Here, we connect these two scales in a joint theoretical model.
Results: We developed a highly parallel version of the cellular Potts model that can be flexibly applied and provides an agent-based model driving cellular events. The model can be modular extended to a multi-model simulation on both scales. Based on the NAStJA framework, a scaling implementation running efficiently on high-performance computing systems was realized. We demonstrate independence of bias in our approach as well as excellent scaling behavior.
Conclusions: Our model scales approximately linear beyond 10,000 cores and thus enables the simulation of large-scale three-dimensional tissues only confined by available computational resources. The strict modular design allows arbitrary models to be configured flexibly and enables applications in a wide range of research questions. Cells in Silico (CiS) can be easily molded to different model assumptions and help push computational scientists to expand their simulations to a new area in tissue simulations. As an example we highlight a 1000 3 voxel-sized cancerous tissue simulation at sub-cellular resolution.
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