Modular Design of Multiscale Models

Availability of biomedical data sets across spatial and temporal scales makes it possible to calibrate complex models that capture integrated processes from the molecular to the whole organism level. This complexity poses multiple challenges related to mathematical modeling, software design, validation, reproducibility, and extensibility. Visualization of model features and dynamics is a key factor in the usability of models by domain experts, such as experimental biologists and clinicians. The proposed project addresses these challenges in the context of the immune response to an important respiratory fungal infection. Its goal is to develop a novel modular approach to model architecture, using a recently introduced technology of lightweight virtual machines and our user-friendly open-source platform for creating complex modular models in a transparent fashion. A key benefit of software containers is that they can encompass the entire computational environment of a model, enabling unprecedented reproducibility of computational results. The overarching computational goal is to develop a novel approach to the modular design of multiscale models.

Modular Design Benefits
Modular design framework enhancements over conventional model structure.

Research Support

  • National Institutes of Health 1U01EB024501-01; 9/20/2017-8/31/2022.

Selected Publications

  • Masison, J., J. Beezley, Y. Mei, H. a. L. Ribeiro, A. C. Knapp, L. Sordo Vieira, B. Adhikari, et al. “A Modular Computational Framework for Medical Digital Twins.” Proceedings of the National Academy of Sciences 118, no. 20 (May 18, 2021).
  • Wooten, David J., Jorge Gómez Tejeda Zañudo, David Murrugarra, Austin M. Perry, Anna Dongari-Bagtzoglou, Reinhard Laubenbacher, Clarissa J. Nobile, and Réka Albert. “Mathematical Modeling of the Candida Albicans Yeast to Hyphal Transition Reveals Novel Control Strategies.” Preprint. Systems Biology, January 20, 2021.
  • deAssis Lopes Rebeiro, Henrique, “Modular Design of Agent-Based Models.” In preparation.
  • Knapp, Adam and Mei, Yu (Eric). “Docker-based Modular Design of Models.” In preparation.