Foundations of a Compositional Systems Biology

TL;DR

This paper presents a comprehensive framework for compositional systems biology, emphasizing modular integration of models and data to enable multiscale simulations of cellular systems.

Contribution

It introduces a conceptual framework, standardized schemas, biological templates, and software tools to facilitate modular, scalable, and collaborative modeling in systems biology.

Findings

Developed a graphical framework for interface definition.

Created standardized schemas for model assembly.

Designed biological templates linking molecular to cellular processes.

Abstract

Composition is a powerful principle for systems biology, focused on the interfaces, interconnections, and orchestration of distributed processes to enable integrative multiscale simulations. Whereas traditional models focus on the structure or dynamics of specific subsystems in controlled conditions, compositional systems biology aims to connect these models, asking critical questions about the space between models: What variables should a submodel expose through its interface? How do coupled models connect and translate across scales? How do domain-specific models connect across biological and physical disciplines to drive the synthesis of new knowledge? This approach requires robust software to integrate diverse datasets and submodels, providing researchers with tools to flexibly recombine, iteratively refine, and collaboratively expand their models. This article offers a comprehensive framework to support this vision, including: a conceptual and graphical framework to define interfaces and composition patterns; standardized schemas that facilitate modular data and model assembly; biological templates that integrate detailed submodels that connect molecular processes to the emergence of the cellular interface; and user-friendly software interfaces that empower research communities to construct and improve multiscale models of cellular systems. By addressing these needs, compositional systems biology will foster a unified and scalable approach to understanding complex cellular systems.