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Finding your inner modeler: An NSF-sponsored workshop to introduce cell biologists to modeling/computational
David E Stone1, Elizabeth S Haswell2, Elizabeth Sztul3
1Department of Biological Sciences, University of Illinois at Chicago, Molecular Biology Research Building, Chicago, IL, USA.
Cellular Logistics
|January 4, 2018
Summary
Computational modeling can advance cell biology beyond traditional experiments. Workshops bridge the gap for cell biologists, demonstrating how to integrate computational approaches for new discoveries.
Area of Science:
- Cell Biology
- Computational Biology
- Systems Biology
Background:
- Classical cell biology relies on empirical, experiment-by-experiment discovery.
- Despite progress, a complete understanding of complex cellular systems remains elusive.
- Integrating theory and computational approaches is crucial for major advancements.
Purpose of the Study:
- To promote the adoption of computational modeling in cell biology.
- To educate cell biologists on the utility and application of computational modeling.
- To facilitate collaboration between cell biologists and computational modelers.
Main Methods:
- Reporting on a workshop designed for cell biologists with limited modeling experience.
- Addressing key questions regarding the suitability, data requirements, and collaboration for computational modeling.
- Providing a primer on integrating modeling into research.
Main Results:
- The workshop successfully addressed critical concerns of cell biologists regarding computational modeling.
- Key issues discussed included project appropriateness, data needs, finding collaborators, and the value of modeling.
- A foundational understanding for incorporating computational modeling was provided.
Conclusions:
- Computational modeling offers a powerful complementary approach to empirical methods in cell biology.
- Workshops are effective in demystifying and promoting the use of computational modeling.
- Bridging the gap between traditional and computational approaches is essential for future cell biology research.
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