| contributor author | Rabiei, Manoochehr | |
| contributor author | McColloch, Andrew | |
| contributor author | Rabbani, Parisa | |
| contributor author | Cho, Michael | |
| contributor author | Bowling, Alan | |
| date accessioned | 2022-02-04T22:12:36Z | |
| date available | 2022-02-04T22:12:36Z | |
| date copyright | 9/28/2020 12:00:00 AM | |
| date issued | 2020 | |
| identifier issn | 1555-1415 | |
| identifier other | manu_142_11_110817.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4275100 | |
| description abstract | Biomolecular 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. | |
| publisher | The American Society of Mechanical Engineers (ASME) | |
| title | Long Term Dynamic Simulation of a Stem Cell Nucleus | |
| type | Journal Paper | |
| journal volume | 15 | |
| journal issue | 11 | |
| journal title | Journal of Computational and Nonlinear Dynamics | |
| identifier doi | 10.1115/1.4048195 | |
| journal fristpage | 0111002-1 | |
| journal lastpage | 0111002-15 | |
| page | 15 | |
| tree | Journal of Computational and Nonlinear Dynamics:;2020:;volume( 015 ):;issue: 011 | |
| contenttype | Fulltext | |