Multi-class and multi-scale models of complex biological phenomena

Jessica S. Yu, Neda Bagheri*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

22 Scopus citations


Computational modeling has significantly impacted our ability to analyze vast (and exponentially increasing) quantities of experimental data for a variety of applications, such as drug discovery and disease forecasting. Single-scale, single-class models persist as the most common group of models, but biological complexity often demands more sophisticated approaches. This review surveys modeling approaches that are multi-class (incorporating multiple model types) and/or multi-scale (accounting for multiple spatial or temporal scales) and describes how these models, and combinations thereof, should be used within the context of the problem statement. We end by highlighting agent-based models as an intuitive, modular, and flexible framework within which multi-scale and multi-class models can be implemented.

Original languageEnglish (US)
Pages (from-to)167-173
Number of pages7
JournalCurrent Opinion in Biotechnology
StatePublished - Jun 1 2016

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Biomedical Engineering

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