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- Event Type
- Lecture
- Sponsor
- Department of Physics
- Location
- Loomis Lab 144
- Date
- Apr 15, 2022 2:00 pm
- Speaker
- Niall Mangan (McCormick School of Engineering, Northwestern University)
- Contact
- Brandy Koebbe
- E-Mail
- bkoebbe@illinois.edu
- Views
- 81
- Originating Calendar
- Physics - Biological Physics / iPoLS / STC-QCB Seminar
Biological systems such as metabolic and regulatory networks are often well-described using ordinary differential equations to describe mass-action kinetics. Several problems arise while building and constraining these models. For example in metabolic systems the rate-limiting steps can vary depending on the experimental conditions. This can lead to uncertainty in the appropriate model structure to describe a system and in the identifiability of the model prameters. In principle we would like to build models which capture these rate limiting steps in a principled way and where either all parameters can be identified or the uncertainty is charactered. I will describe our work on different approaches to building models from dynamic data, including methods for sparse model selection and parameter estimation for system where only a subsets of the variables are directly measured.