Complex Adaptive Systems and Computational Biology

We are interested in the informational properties of natural and artificial systems, which enable them to adapt and evolve. This means both producing computational models of biological systems to understand the evolutionary role of information, as well as abstracting principles from biology to produce adaptive information technology. Our current research projects are on complex dynamics in biological networks (gene regulation, cell signalling, and metabolic networks), text and literature mining (in proteomics, protein-protein interaction and pharmokinetics), computational social science, complex networks, machine learning, computational models of RNA editing, artificial immune systems, evolutionary systems, artificial life, cognitive science, and biosemiotics.