Towards design space exploration for biological systems

For both embedded systems and biological cell systems, design is a feature that defines their identity. The assembly of different components in designs of both systems can vary widely. Given the similarities between computers and cellular systems, methods and models of computation from the domain of computer systems engineering could be applied to model cellular systems. Our aim is to construct a framework that focuses on understanding the design options and consequences within a cell, taking an in-silico (forward-) engineering approach rather than the reverse-engineering approach now used by default in this domain. We take our ideas from the domain of embedded computer systems. The most important features of our approach, as taken from this domain, are a variable abstraction level of model components that allows for inclusion of components of which detailed information is lacking, and a separation of concerns between function and performance by components in the design. This allows for efficient and flexible modeling. Also, there is a strict separation between computation within and communication between components, thus reducing complexity. As a proof-of-principle, we show that we can make a statement regarding the design of the gene expression machinery of a cell to produce a protein, using such a method.