Computational modeling has emerged as a powerful tool to understand the dynamics of complex biological systems such as the immune system.  MIEP aims to characterize in a comprehensive way novel mechanisms of immune modulation in the gut mucosa by constructing mathematical/computational models of immune responses to enteric pathogens that are firmly grounded on immunological experimentation.

The MIEP modeling process involves:

1. Generation of the structural model based on a literature search
2. Compilation of a calibration database using literature data sets
3. Model fitting to the experimental data via a calibration process
4. In silico experimentation to generate model-derived predictions
5. Validation of model-derived predictions through experimental testing
6. Model refinement by feeding newly generated experimental data back to the model
7. Generation of novel hypotheses

MIEP will also provide immunologists and infectious disease experts novel ways to study the immune system by making computational solutions easily accessible and user-friendly. MIEP will make computational resources seamless, invisible for routine analytical efforts and organize them as an evolving commodity that serves the immunology and infectious disease communities.