Abstract
Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level.
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Acknowledgments
We thank Paul Wolberg and Joe Waliga for computational assistance. This research was supported in part through computational resources and services provided by Advanced Research Computing at the University of Michigan, Ann Arbor. This research was funded by the following NIH Grants: R01 EB012579 (DEK and JJL) and R01 HL 110811 (DEK and JJL).
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Nicholas Cilfone, Denise Kirschner, and Jennifer Linderman declare no conflicts of interests.
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Cilfone, N.A., Kirschner, D.E. & Linderman, J.J. Strategies for Efficient Numerical Implementation of Hybrid Multi-scale Agent-Based Models to Describe Biological Systems. Cel. Mol. Bioeng. 8, 119–136 (2015). https://doi.org/10.1007/s12195-014-0363-6
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DOI: https://doi.org/10.1007/s12195-014-0363-6