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dc.contributor.authorRabiei, Manoochehr
dc.contributor.authorMcColloch, Andrew
dc.contributor.authorRabbani, Parisa
dc.contributor.authorCho, Michael
dc.contributor.authorBowling, Alan
dc.date.accessioned2022-02-04T22:12:36Z
dc.date.available2022-02-04T22:12:36Z
dc.date.copyright9/28/2020 12:00:00 AM
dc.date.issued2020
dc.identifier.issn1555-1415
dc.identifier.othermanu_142_11_110817.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4275100
dc.description.abstractBiomolecular simulations are computationally expensive. Simulating time histories larger than seconds remain elusive even with the help of supercomputers. Biological phenomena are multiscale in nature. The dynamics range from atomistic to microscale. Herein a recently developed scaling approach, based on the method of multiple scales (MMS), is used to accomplish a long term simulation of a subcellular system. The first key advantage of this approach is the drastic reduction in computational time. This approach is illustrated using a mesenchymal stem cell (MSC) as it undergoes adipogenic differentiation, a process that takes 15 days, which was simulated in less than 1.5 h on a typical desktop computer. The second key advantage of the high-speed simulation is that it facilitates the study of mechanical properties, such as nucleus membrane stiffness, that are difficult to measure experimentally with certainty.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleLong Term Dynamic Simulation of a Stem Cell Nucleus
dc.typeJournal Paper
dc.journal.volume15
dc.journal.issue11
dc.journal.titleJournal of Computational and Nonlinear Dynamics
dc.identifier.doi10.1115/1.4048195
dc.journal.fristpage0111002-1
dc.journal.lastpage0111002-15
dc.page15
dc.treeJournal of Computational and Nonlinear Dynamics:;2020:;volume( 015 ):;issue: 011
dc.contenttypeFulltext


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