Interactively illustrating polymerization using three-level model fusion

Ivan Kolesar*, Julius Parulek, Ivan Viola, Stefan Bruckner, Anne Kristin Stavrum, Helwig Hauser

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Background: Research in cell biology is steadily contributing new knowledge about many aspects of physiological processes, both with respect to the involved molecular structures as well as their related function. Illustrations of the spatio-temporal development of such processes are not only used in biomedical education, but also can serve scientists as an additional platform for in-silico experiments. Results: In this paper, we contribute a new, three-level modeling approach to illustrate physiological processes from the class of polymerization at different time scales. We integrate physical and empirical modeling, according to which approach best suits the different involved levels of detail, and we additionally enable a form of interactive steering, while the process is illustrated. We demonstrate the suitability of our approach in the context of several polymerization processes and report from a first evaluation with domain experts. Conclusion: We conclude that our approach provides a new, hybrid modeling approach for illustrating the process of emergence in physiology, embedded in a densely filled environment. Our approach of a complementary fusion of three systems combines the strong points from the different modeling approaches and is capable to bridge different spatial and temporal scales.

Original languageEnglish (US)
Article number345
JournalBMC BIOINFORMATICS
Volume15
Issue number1
DOIs
StatePublished - Oct 14 2014
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2014 Kolesar et al.

Keywords

  • Biochemical visualization
  • L-system modeling
  • Multi-agent modeling
  • Polymerization
  • Visualization of physiology

ASJC Scopus subject areas

  • Structural Biology
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

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