They are based on available knowledge and may provide insight into interactions. However the model's results are based on the original assumptions. Mathematical models can be used to compare and contrast existing controversies, extend intuition about biological process, and can be done without data. Creating models generally requires input from many disciplines. Models may be able to provide details or understanding about an experimental system.
Differential equations are a major component of the models.
Parameters in models represent rate constants of the processes. They can help identify key interactions, and allow for sensitivity and uncertaintly analyses as well as aid in obtaining bifurcation information. These methods can lead to a greater understanding of the important porcesses of the biological system. Because of the nature of these parameters, it is easy to perturb the system to explore changes in the biological assumptions. Applications which are already underway include models for control strategies of TB epidemics and models to understand the dynamics of HIV infection including, production, turnover, half-life, and possible reservoirs of infection.