Complex Systems

Self-organising and self-assembling processes are ubiquitous in the natural world. Understanding how nature produces and relies upon these processes is of enormous scientific and technical relevance. A deeper understanding of the fundamentals of molecular self-assembly all the way up to the self-organisation of biological processes is set to profoundly affect the way we engineer systems, and more specifically, computational or informational ones. That is, self-assembly and self-organisation, ubiquitous natural processes, are likely to become key engineering tools in the quest for faster, cheaper, smaller and pervasive information processing platforms.

These phenomena are potentially advantageous fabrication and control processes because, with an appropriate set of components and associated interactions, they will autonomously, robustly and efficiently assemble into a desired system without recurring to a centralised (e.g. top-down) control. Robustness and versatility are some of the most important properties of self-organising and self-assembling natural systems and this makes them an even more appealing engineering methodology.

Thus, as the complexity of our societies and the grand challenges that affect them (e.g. climate change, food security, ageing population) grow faster than our capacity to engineer solutions to tackle them, a radical new research agenda must be put in place that will embrace (rather than shy away from) the complexity.

The ICOS group researches algorithms for the analysis, visualisation and engineering of complex systems ranging from molecular interaction complex networks (e.g. gene interaction networks, protein-protein networks, synthetic gene networks), through complex brain circuitry networks all the way to complex software systems.