Abstract
The immune system is modeled by way of a system of ordinary differential equations involving a large number of parameters, such as growth rates and initial conditions. Key to successful implementation of the model is the estimation of such parameters from available data. A parameter search algorithm based on linear codes is developed having as aim the identification of different regimes of behaviour of the model, the estimation of parameters in a high dimensional space, and the model calibration to data.
| Original language | English |
|---|---|
| Pages (from-to) | 155-171 |
| Number of pages | 17 |
| Journal | Computational Optimization and Applications |
| Volume | 42 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2009 |
| Externally published | Yes |
Keywords
- Differential equations
- Dynamical system modeling
- Immune system
- Optimization