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@ARTICLE{Berghoff:884066,
      author       = {Berghoff, Marco and Rosenbauer, Jakob and Hoffmann, Felix
                      and Schug, Alexander},
      title        = {{C}ells in {S}ilico – introducing a high-performance
                      framework for large-scale tissue modeling},
      journal      = {BMC bioinformatics},
      volume       = {21},
      number       = {1},
      issn         = {1471-2105},
      address      = {Heidelberg},
      publisher    = {Springer},
      reportid     = {FZJ-2020-03075},
      pages        = {436},
      year         = {2020},
      abstract     = {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 10003 voxel-sized
                      cancerous tissue simulation at sub-cellular resolution.},
      cin          = {JSC / NIC},
      ddc          = {610},
      cid          = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)NIC-20090406},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / Forschergruppe Schug $(hkf6_20200501)$ / PhD no
                      Grant - Doktorand ohne besondere Förderung
                      (PHD-NO-GRANT-20170405)},
      pid          = {G:(DE-HGF)POF3-511 / $G:(DE-Juel1)hkf6_20200501$ /
                      G:(DE-Juel1)PHD-NO-GRANT-20170405},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:33023471},
      UT           = {WOS:000578451600002},
      doi          = {10.1186/s12859-020-03728-7},
      url          = {https://juser.fz-juelich.de/record/884066},
}