Life sciences through mathematical models
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This article discusses some of the basic principles of mathematical modeling in life sciences, and in particular the special features that make the modeling task fundamentally different from the traditional reductive modeling. The intricacies of the modeling in living systems are elucidated by simple and tractable examples that underline the problems of parametric models and the issue of non-scalability of the models.
KeywordsComplex systems Parametric models Agent-based models Computational statistics
The work of Daniela Calvetti was partly supported by Grant number 246665 from the Simons Foundation, and the work of Erkki Somersalo was partly supported by NSF Grant DMS 1016183.
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