Computational Approaches for Multiscale Modeling

Z. Wang, V. Cristini, T. S. Deisboeck

Research output: Chapter in Book/Report/Conference proceedingChapter


Quantitative, predictive multiscale models show promise in accurately representing the behavior of complex biological systems across a wide range of spatial and temporal scales based on experimental and clinical data. Eventually, this allows for data integration, hypothesis generation, and prediction, and thus has the potential to significantly impact biomedical research. Biological processes can occur at the same scale as well as between scales, forming a complex system with multiple feedback and feed-forward loops. Advanced multiscale methods are therefore needed to begin to address these challenges. In this article, we discuss current advances in the development of multiscale modeling methods. We also discuss some key points in multiscale modeling-aided biomedical research.

Original languageEnglish (US)
Title of host publicationSystems Cell Biology
Number of pages6
ISBN (Electronic)9780123944474
ISBN (Print)9780123947963
StatePublished - Jan 1 2016


  • Adaptive hybrid modeling
  • Agent-based modeling
  • Computer simulation
  • Continuum modeling
  • Discrete modeling
  • Drug target
  • Dynamic density functional theory
  • Equation-free approach
  • Hypothesis generation
  • Integrative approach
  • Mean field theory
  • Molecular signaling network
  • Tumor growth and development

ASJC Scopus subject areas

  • Medicine(all)


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