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@INPROCEEDINGS{Berghoff:874346,
      author       = {Berghoff, Marco and Rosenbauer, Jakob and Schug, Alexander},
      title        = {{M}assively {P}arallel {L}arge-{S}cale {M}ulti-{M}odel
                      {S}imulation of {T}umour {D}evelopment {I}ncluding
                      {T}reatments},
      volume       = {50},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
      reportid     = {FZJ-2020-01379},
      isbn         = {978-3-95806-443-0},
      series       = {Publication Series of the John von Neumann Institute for
                      Computing (NIC) NIC Series},
      pages        = {63 - 71},
      year         = {2020},
      comment      = {NIC Symposium 2020},
      booktitle     = {NIC Symposium 2020},
      abstract     = {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.},
      month         = {Feb},
      date          = {2020-02-27},
      organization  = {NIC Symposium 2020, Jülich (Germany),
                       27 Feb 2020 - 28 Feb 2020},
      cin          = {NIC},
      cid          = {I:(DE-Juel1)NIC-20090406},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / PhD no Grant - Doktorand ohne besondere
                      Förderung (PHD-NO-GRANT-20170405)},
      pid          = {G:(DE-HGF)POF3-511 / G:(DE-Juel1)PHD-NO-GRANT-20170405},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      url          = {https://juser.fz-juelich.de/record/874346},
}