A simulation methodology in modeling cell divisions with stochastic effects

  • Authors:
  • Harsha K. Rajasimha;David C. Samuels;Richard E. Nance

  • Affiliations:
  • Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA;Virginia Bioinformatics Institute, Virginia Tech Blacksburg, VA;Virginia Tech, Blacksburg, VA

  • Venue:
  • WSC '04 Proceedings of the 36th conference on Winter simulation
  • Year:
  • 2004

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Abstract

We present a model to explain the effects of the long time between blood stem cell divisions and rapid cascades of progenitor cell divisions on the mitochondrial DNA drift. We allow four stochastic events in the system namely, mtDNA replication and degradation, cell division and death. To implement the conceptual model, we design two simulation models; one for a limited number of stem cells (20,000) over very long time scale (100 years) and another for the cell divisions of a progenitor cell resulting in a large number of blood cells (~10 million) over a shorter time span (25 days). Iterative enhancement with incremental builds constitutes the modeling methodology. We adopt the activity scanning conceptual framework for the model implementation. Initial transient and memory issues are resolved. By output data analysis, we conclude that the variation in mutation level occurs significantly due to time and less so due to cell divisions.