From food chains to airline route maps, complex networks are ubiquitous. Complex networks are a particularly powerful way to study biological systems, for which the quantity of data available has exploded recently, for example through genome projects, the human connectome project and protein data banks. These systems’ intricate structures and dynamics routinely span multiple temporal and spatial scales, defying ‘bottom-up’ attempts to describe them. The potency of networks to traverse these scales is one of the most exciting aspects of complex network research.
In July 2016, I began a postdoctoral position in Prof. Ed Bullmore’s group in Cambridge, working on network approaches to study structural and functional MRI brain images. A key focus of my work is the PSYSCAN project, which is an international EU project and aims to develop and validate imaging biomarkers for psychosis. My role is to assemble network analysis methods to diagnose and predict the psychosis trajectories of individual patients. I also lead a project at The Alan Turing Institute, investigating the potential of transcribed speech data to predict risk for psychotic disorders.
Prior to this project, I completed my PhD in the Theory of Condensed Matter group at the Cavendish Laboratory (Cambridge Physics Department), where I worked with Dr Alex Chin on the ultrafast photophysics of biological and organic systems. In particular, I worked on modelling proteins as networks and studying light harvesting pigment protein complexes using a novel technique known as 2D electronic spectroscopy. This work resulted in a publication in Nature Chemistry and my thesis was published as a Springer thesis.