Material Detail
Automated detection of chaotic and oscillatory regimes
This video was recorded at 4th International Workshop on Machine Learning in Systems Biology (MLSB), Edinburgh 2010. Qualitative parameter estimation algorithms are a promising but underdeveloped class of inference methods [1]. They offer the ability to infer parameters when only qualitative features of the system are known or need to be specified. Here we adapt the unscented Kalman filter for identification of model parameters that give rise to a desired Lyapunov spectrum. This novel approach extends the reach of these techniques, allowing detection of the most complex and elusive dynamical behaviours. We demonstrate our method on three ODE models, including a simple model of the Hes1 regulatory system.
Quality
- User Rating
- Comments
- Learning Exercises
- Bookmark Collections
- Course ePortfolios
- Accessibility Info
More about this material
- Mobile Compatibility:
- Not specified at this time
- Language:
- English
- Cost Involved:
- No
- Source Code Available:
- No
- Creative Commons:
-
This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States
