Design of a framework for modeling, integration and simulation of physiological models

Area of Science:

• Computational biology
• Physiological modeling
• Systems biology

Background:

• Multiscale physiological models face significant challenges due to high coupling within and across scales.
• Information technology, analytical, and computational tools are crucial for addressing these complexities.
• Existing modeling environments may not adequately support the integration of diverse physiological processes.

Purpose of the Study:

• To present the modular design of the Physiological Model Simulation, Integration and Modeling Framework (Phy-SIM).
• To demonstrate how Phy-SIM facilitates various approaches for multiscale physiological modeling.
• To enhance the development and integration of physiological models through improved tools and mechanisms.

Main Methods:

• Development of a modular, layered architecture for Phy-SIM, separating structure from function.
• Implementation of an ontology-based architecture to link anatomical and physiological information.
• Utilizing information technology and computational tools within the Phy-SIM environment.

Main Results:

• Phy-SIM offers a structured environment for developing and integrating physiological models.
• The layered design promotes modular thinking in physiological process modeling.
• Ontology integration enhances the richness and accuracy of model information.

Conclusions:

• Phy-SIM provides a robust framework for tackling multiscale physiological modeling challenges.
• The modular and ontology-driven design improves the efficiency and effectiveness of model development and integration.
• This approach supports advancements in computational physiology and systems biology research.