A Dynamic Physical Model of Cell Migration, Differentiation and Apoptosis in Caenorhabditis elegans

  • Antje Beyer
  • Ralf Eberhard
  • Nir Piterman
  • Michael O. Hengartner
  • Alex Hajnal
  • Jasmin FisherEmail author
Conference paper
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 736)


The germ line of the nematode C. elegansprovides a paradigm to study essential developmental concepts like stem cell differentiation and apoptosis. Here, we have created a computational model encompassing these developmental landmarks and the resulting movement of germ cells along the gonadal tube. We have used a technique based on molecular dynamics (MD) to model the physical movement of cells solely based on the force that arises from dividing cells. This novel way of using MD to drive the model enables calibration of simulation and experimental time. Based on this calibration, the analysis of our model shows that it is in accordance with experimental observations. In addition, the model provides insights into kinetics of molecular pathways within individual cells as well as into physical aspects like the cell density along the germ line and in local neighbourhoods of individual germ cells. In the future, the presented model can be used to test hypotheses about diverse aspects of development like stem cell division or programmed cell death. An iterative process of evolving this model and experimental testing in the model system C. eleganswill provide new insights into key developmental aspects.


Germ Cell Daughter Cell Germ Line Fertilisation Rate Movement Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We are grateful to James Margetson for contributing an initial environment program in F# on which this model is based and for his support on the usage of F#. Antje Beyer is grateful to Adrian Hemmen for introducing her to the MD framework and for critical and helpful discussions of the model. This work was supported in part by the European Union grant FP7 PANACEA 222936 (Jasmin Fisher, Michael O. Hengartner and Alex Hajnal) and the Swiss National Science Foundation (Michael O. Hengartner). Antje Beyer is funded by Microsoft Research through its PhD Scholarship Programme.


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Antje Beyer
    • 1
  • Ralf Eberhard
    • 2
    • 3
  • Nir Piterman
    • 4
  • Michael O. Hengartner
    • 2
  • Alex Hajnal
    • 2
  • Jasmin Fisher
    • 5
    Email author
  1. 1.Department of GeneticsUniversity of CambridgeCambridgeUK
  2. 2.Institute of Molecular Life SciencesUniversity of ZurichZurichSwitzerland
  3. 3.PhD Program in Molecular Life Sciences, Life Science Zurich Graduate School and MD/PhD ProgramUniversity of ZurichZurichSwitzerland
  4. 4.Department of Computer ScienceUniversity of LeicesterLeicesterUK
  5. 5.Microsoft ResearchCambridgeUK

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