Bridging intracellular scales by mechanistic computational models

Area of Science:

• Cellular and Molecular Biology
• Systems Biology
• Computational Biology

Background:

• Intracellular spatial organization significantly impacts cellular processes like signaling, extending beyond traditional compartments.
• A comprehensive understanding of cellular systems necessitates quantitative models addressing scales of time, molecular abundance, and spatial dimensions.

Purpose of the Study:

• To review recent advancements in multi-scale modeling for cellular systems.
• To identify challenges in developing mechanistic mathematical models that integrate diverse scales.

Main Methods:

• Developing mechanistic mathematical models that span multiple scales.
• Combining microscopic representations of chemical reactions with continuum dynamics.
• Addressing challenges in computational tractability for large-scale simulations.

Main Results:

• Recent progress has been made in bridging different levels of description in multi-scale models.
• Models increasingly integrate spatial organization, molecular dynamics, and temporal aspects.
• Key challenges remain in areas like active transport and dynamic cellular geometries.

Conclusions:

• Multi-scale modeling is essential for a quantitative, mechanistic understanding of cellular systems.
• Future research should focus on overcoming challenges in active transport and dynamic geometries within these models.
• Integrating spatial, temporal, and molecular scales is vital for advancing systems biology.