The Ninth q-bio Summer School - Albuquerque: Lecture 22

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Title: Parameter estimation, sensitivity analysis, and sloppiness in systems biology

Lecturer: Ryan N. Gutenkunst

Abstract: Quantitative simulations of biological systems typically contain many numerical parameters, such as rate constants and protein concentrations. In some cases, values for these parameters can be found in the literature or inferred directly. The dirty secret of systems biology, however, is that often these parameters must be inferred indirectly, and this is a non-trivial task. In this session, we will discuss how to fit models to estimate unmeasured parameters and how to assess the sensitivity of your results and predictions to those unmeasured parameters. We will also discuss sloppiness, a seemingly universal phenomenon that suggests modelers should focus less on confidently inferred parameter values and more on confident predictions.

Slides: The slides for this lecture are available here.