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| Hauptseite > Publikationsdatenbank > Massively Parallel Large-Scale Multi-Model Simulation of Tumour Development Including Treatments > print |
| Hauptseite > Publikationsdatenbank > Massively Parallel Large-Scale Multi-Model Simulation of Tumour Development Including Treatments > print |
| 001 | 874346 | ||
| 005 | 20231023123818.0 | ||
| 020 | _ | _ | |a 978-3-95806-443-0 |
| 024 | 7 | _ | |2 Handle |a 2128/24450 |
| 037 | _ | _ | |a FZJ-2020-01379 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |0 P:(DE-HGF)0 |a Berghoff, Marco |b 0 |
| 111 | 2 | _ | |a NIC Symposium 2020 |c Jülich |d 2020-02-27 - 2020-02-28 |w Germany |
| 245 | _ | _ | |a Massively Parallel Large-Scale Multi-Model Simulation of Tumour Development Including Treatments |
| 260 | _ | _ | |a Jülich |b Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag |c 2020 |
| 295 | 1 | 0 | |a NIC Symposium 2020 |
| 300 | _ | _ | |a 63 - 71 |
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| 490 | 0 | _ | |a Publication Series of the John von Neumann Institute for Computing (NIC) NIC Series |v 50 |
| 520 | _ | _ | |a The temporal and spatial resolution in the microscopy of tissues has increased significantly within the last years, yielding new insights into the dynamics of tissue development and the role of single cells within it. Still, the theoretical description of the connection of single cell processes to macroscopic tissue reorganisations is lacking. Especially in tumour development, single cells play a crucial role in the advance of tumour properties. We developed a simulation framework that can model tissue development up to the centimetre scale with micrometre resolution of single cells. Through parallelisation, it enables the efficient use of high-performance computing systems, therefore enabling detailed simulations on 10.000s of cores. Our generalised tumour model respects adhesion driven cell migration, cell-to-cell signalling, and mutation-driven tumour heterogeneity. We scan the response of the tumour development depending on division inhibiting substances such as cytostatic agents. Furthermore, we are investigating the interaction with radiotherapy to find a suitable therapy plan. Currently, the emergence of ever-more-powerful experimental techniques such as light sheet microscopy already offers unprecedented subcellular insight into tissue dynamics. Combined with powerful machine learning techniques, such large data sets (TB’s +) can be effectively evaluated promising realistic parameters for our simulations for topics ranging from cancer development to embryogenesis or morphogenesis with considerable impact both for basic science and applied biomedical fields. |
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| 536 | _ | _ | |0 G:(DE-Juel1)PHD-NO-GRANT-20170405 |a PhD no Grant - Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405) |c PHD-NO-GRANT-20170405 |x 1 |
| 700 | 1 | _ | |0 P:(DE-Juel1)174346 |a Rosenbauer, Jakob |b 1 |
| 700 | 1 | _ | |0 P:(DE-Juel1)173652 |a Schug, Alexander |b 2 |e Corresponding author |
| 787 | 0 | _ | |0 FZJ-2020-01353 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/874346/files/NIC_2020_Schug.pdf |y OpenAccess |
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