  Composition is a powerful principle for systems biology, focused on the
interfaces, interconnections, and orchestration of distributed processes.
Whereas most systems biology models focus on the structure or dynamics of
specific subsystems in controlled conditions, compositional systems biology
aims to connect such models into integrative multiscale simulations. This
emphasizes the space between models--a compositional perspective asks what
variables should be exposed through a submodel's interface? How do coupled
models connect and translate across scales? How can we connect domain-specific
models across biological and physical research areas to drive the synthesis of
new knowledge? What is required of software that integrates diverse datasets
and submodels into unified multiscale simulations? How can the resulting
integrative models be accessed, flexibly recombined into new forms, and
iteratively refined by a community of researchers? This essay offers a
high-level overview of the key components for compositional systems biology,
including: 1) a conceptual framework and corresponding graphical framework to
represent interfaces, composition patterns, and orchestration patterns; 2)
standardized composition schemas that offer consistent formats for composable
data types and models, fostering robust infrastructure for a registry of
simulation modules that can be flexibly assembled; 3) a foundational set of
biological templates--schemas for cellular and molecular interfaces, which can
be filled with detailed submodels and datasets, and are designed to integrate
knowledge that sheds light on the molecular emergence of cells; and 4)
scientific collaboration facilitated by user-friendly interfaces for connecting
researchers with datasets and models, and which allows a community of
researchers to effectively build integrative multiscale models of cellular
systems.
