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On Validation and Invalidation of Biological Models

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Given multiple models of a biological system and some experimental data, how can one determine which is the correct model? In this talk we show that such a question is in fact ill-posed and that the best that can be done is to invalidate a given model. Using techniques from convex optimization and real algebraic geometry we will show how both uncertain continuous and discrete time dynamical system models can be invalidated in the presence of experimental data. The ideas presented will be illustrated through simple biochemical reaction network examples.

This talk is part of the Cambridge Systems and Synthetic Biology Study Group series.

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