The Cell Physiome: What Do We Need in a Computational Physiology Framework for Predicting Single-Cell Biology?

Area of Science:

• Computational Biology
• Biophysics
• Systems Biology

Background:

• Modern biology faces a data explosion, requiring advanced computational tools for cellular mechanistic insights.
• Existing models often lack the spatial detail and biophysical basis needed to fully understand cell physiology.

Purpose of the Study:

• To introduce the Cell Physiome Project, a framework for developing, sharing, and utilizing biophysics-based computational models of single-cell physiology.
• To highlight the necessity of spatially detailed, biophysics-based models for uncovering novel cell biology mechanisms.

Main Methods:

• Utilizing bond graphs for efficient creation of integrated cell physiome models.
• Demonstrating model applications in calcium signaling, bioenergetics, and endosomal trafficking.
• Reviewing current progress and challenges in cell physiome model development.

Main Results:

• Bond graphs facilitate the integration of chemical, mechanical, electromagnetic, and thermal processes.
• Models maintain essential mass and energy balance.
• Bond graphs promote modularization and reusability for large-scale cell modeling.

Conclusions:

• The Cell Physiome Project provides a scalable approach to mechanistic biomedical data science.
• Bond graphs are a key enabling technology for creating comprehensive cell physiome models.
• Further development is needed to fully realize the potential of this field.