A platform for in silico modeling of physiological systems III

Area of Science:

• Physiology
• Systems Biology
• Computational Biology

Background:

• Physiome and systems biology integrate biological knowledge across scales.
• Developing physiologically plausible, sharable mathematical models is crucial for dynamic simulations.
• Existing platforms may lack comprehensive support for multi-scale, multi-level modeling and data integration.

Purpose of the Study:

• To introduce new features of the insilicoML (ISML) and insilicoIDE (ISIDE) open platform.
• To enhance capabilities for integrating experimental data into dynamic simulations.
• To expand the range of model types supported by the platform.

Main Methods:

• Enhancements to ISML/ISIDE for incorporating time-series and morphological data.
• Development of dynamic simulation capabilities driven by experimental data.
• Extension of ISML to describe new model types, including multi-agent systems and partial differential equation (PDE) models.
• Implementation of finite element method (FEM) for solving PDE models within ISIDE.

Main Results:

• Improved ability to integrate diverse experimental data (time-series, morphological) with dynamic simulations.
• Expanded support for advanced modeling paradigms, including multi-agent systems.
• Successful implementation of PDE models solved via FEM for physiological simulations.
• Enhanced platform facilitates reuse, construction, and simulation of physiological models.

Conclusions:

• The updated ISML/ISIDE platform offers advanced features for physiological modeling and simulation.
• The platform's enhanced data integration and model variety support multi-scale and multi-level systems biology research.
• ISML/ISIDE provides a robust, open environment for advancing physiome research through computational modeling.