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- W4212929624 abstract "In biology and bioengineering, mathematical and statistical analysis provides an understanding of biological systems that enables their control and manipulation. Tailoring mathematical and experimental complexity to the biological question of interest is crucial to avoid issues relating to parameter identifiability. We develop models and tools to bring new data-based insights to a range of contemporary problems in biology and bioengineering. These include data-focused stochastic models that describe complex cell interactions and decision making, incorporating biological systems into new engineered materials, and new tools to diagnose parameter identifiability and guide model complexity for stochastic differential equation models." @default.
- W4212929624 created "2022-02-24" @default.
- W4212929624 creator A5006197836 @default.
- W4212929624 date "2022-02-21" @default.
- W4212929624 modified "2023-09-25" @default.
- W4212929624 title "Model complexity in biology and bioengineering" @default.
- W4212929624 doi "https://doi.org/10.5204/thesis.eprints.227787" @default.
- W4212929624 hasPublicationYear "2022" @default.
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