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Seven challenges in the multiscale modeling of multicellular tissues
Alexander G Fletcher1,2, James M Osborne3
1School of Mathematics and Statistics, University of Sheffield, Sheffield, UK.
Wires Mechanisms of Disease
|January 13, 2022
Summary
Multiscale computational models are crucial for understanding how cell behaviors create tissue dynamics in developmental biology and regenerative medicine. This review summarizes progress and challenges in these complex modeling approaches.
Area of Science:
- Multiscale modeling
- Developmental biology
- Tissue engineering
- Regenerative medicine
Background:
- Multicellular tissue growth and dynamics rely on coordinated cell behaviors (shape changes, movement, division) regulated by subcellular machinery and signaling.
- Understanding how scale relationships yield emergent tissue-level behaviors is a key challenge in biology and medicine.
Purpose of the Study:
- To review recent advancements in multiscale modeling of multicellular tissues.
- To identify and discuss ongoing challenges in constructing, implementing, interrogating, and validating these models.
Main Methods:
- Integration of molecular biology, live-imaging, and ex vivo experimental data.
- Development of computational models spanning multiple spatial and temporal scales.
- Coupling of cell shape, growth, mechanics, and signaling within models.
Main Results:
- Recent experimental techniques have significantly enhanced the study of tissue dynamics.
- Computational models are increasingly integrating diverse biological processes across scales.
- Significant mathematical and computational challenges persist in multiscale model integration.
Conclusions:
- Multiscale modeling is essential for a comprehensive understanding of tissue dynamics.
- Addressing current challenges is critical for advancing developmental biology, tissue engineering, and regenerative medicine.
- Further development in computational approaches is needed to fully leverage experimental data.
