Interaction Computing (IC) takes inspiration from cellular processes rather than from evolution. BIOMICS aims to leverage existing cell metabolic and regulatory mechanisms as the ontogenetic basis of a model for IC. However, because the knowledge to properly mimic, exploit and adapt these systems to computer science is lacking, BIOMICS will also advance the state of the art in the mathematics of biocomputing. The mathematical structure thus uncovered feeds into two different and complementary directions. On the one hand, it will inform the automata theory formalisms for IC; on the other hand, it will be mapped through category theory to the logic foundations of the BIOMICS specification language. Whereas the automata theory research will focus on the structural properties of self-organising systems, the BIOMICS specification language will instead focus on the specification of self-organising behaviour. By end of Year 2 we will have developed the formal tools and frameworks from both points of view of the behaviour-realisation dichotomy to be able to effect their synthesis in the form of an environment which, through interactions, is capable of generating useful software systems that match the biological structure template – and are therefore themselves based on interactions. This foundational mathematical work of BIOMICS will be applicable to software systems of a radically new kind and to systems biology, creating a unified mathematical framework for understanding, predicting, manipulating, and dynamically synthesising algorithmic activity-in-context based on interactions (i.e. interaction computation) in both realms. This will be demonstrated not only by the application of the framework to the analysis of complex-adaptive biological systems beyond those studied in the course of its development, but also by proof-of-concept implementations of software systems (for example demonstrating security properties) as a potential new paradigm for unconventional computing.