(Project will start in 2018)
Synthetic biology aims at the design of biological systems in a systematic way, a process whose hallmark characteristics closely resemble the composition of software: off-the-shelf parts and devices with standard connections, the usual ingredients for assembling components into increasingly complex systems.
Of course, a number of key enabling technologies are specifically biological, for example, DNA sequencing and fabrication. But, on the other hand, there is also a need for new models to cope with the complex and heterogeneous nature of biological systems. In this context, our starting point is to regard a network of interacting genes and proteins as a dynamic system evolving in time according to fundamental laws of reaction, diffusion and transport. These laws govern how a regulatory network, confronted by any set of stimuli, determines the appropriate response of a cell. This information processing system can be described in precise mathematical terms, resorting to state-of-art research on hybrid systems: transition systems, as typically studied in reactive software, but combining discrete, continuous and stochastic features. The corresponding notions of emerging behaviour, and techniques to express, analyse and verify both structural and behavioural properties, may bring a new understanding to this domain.
However, both fundamental and applied research is deeply needed here. On the one hand, such models and techniques are still an open domain. KLEE adopts a specific perspective: that of the theory of coalgebras, popularised as the "mathematics of transition systems" which provides a general way to express, reason and interrelate different notions of transition, shape and behaviour. Hybrid models, however, are notoriously hard to analyse and verify. In particular, there is a lack of tools for combining stochastic and physical constraints and to (automatically) transform non-computational models into efficient computational ones. On the other hand, if components are well understood in Software Engineering, such is not the case in biological systems. Bio devices, no matter how efficiently designed, develop over time highly complex and unforeseen interactions and redundancies.
Thus, the project will focus on:
The project builds on the team's work for the last four years on coalgebraic software components. Given its interdisciplinary nature, a researcher in synthetic biology, in cooperation with the BIOCORE team at INRIA, joined. A start-up company, SilicoLife, specialized on industrial biotechnology applications, will assess our results and methods.