FAMoS

FAMoS identifies dynamical models for complex biological systems by searching large model spaces to elucidate factors and processes underlying system dynamics.

Key Features:

• Dynamic Model Selection: Employs a dynamic search strategy to navigate large model spaces without exhaustive enumeration.
• Local and Non-Local Search Methods: Combines local search techniques with non-local methods to avoid entrapment in local minima and to explore structurally similar models.
• Flexibility and Adaptability: Accommodates diverse model structures for application across varied biological problems and experimental data types.

Scientific Applications:

• Validation: Validated on both simulated and experimental datasets.
• Immune cell proliferation analysis: Applied to CD4+ and CD8+ T cell proliferation data, identifying reduced proliferation potential in tissue-like 3D ex vivo cultures compared to suspension.

Methodology:

Searches large model spaces using advanced local and non-local search strategies to prevent local minima and to consider structurally similar processes.