Introduction to Computational Modeling of Multicellular Tissues.

Area of Science:

• Computational Biology
• Biophysics
• Multiscale Modeling

Background:

• Biological tissues exhibit complex mechanisms across diverse temporal and spatial scales.
• Tissue analysis necessitates advanced mathematical, computational, and software development skills.
• Computational modeling is crucial for understanding tissue behavior.

Purpose of the Study:

• To introduce fundamental concepts and challenges in biological tissue modeling.
• To explain the representation and coupling of chemical and cellular properties in virtual tissues.
• To demonstrate reproducible tissue modeling using the Multicell Python library.

Main Methods:

• Focus on integrating chemical and cellular properties for virtual tissue construction.
• Utilize the Multicell Python library for implementation and simulation.
• Provide examples accessible to users with limited biological modeling experience.

Main Results:

• A framework for representing and coupling diverse tissue properties is presented.
• The Multicell library facilitates the creation of virtual tissues with integrated functionalities.
• Demonstrated ease of reproducibility for biological modeling tasks.

Conclusions:

• Tissue modeling is essential for understanding complex biological systems.
• The Multicell library offers a user-friendly approach to virtual tissue modeling.
• This work lowers the barrier to entry for researchers in biological modeling.