I am a PhD student at the University of Manchester Faculty of Life Sciences. I am funded by a CASE award with industry partner Pfizer. I have a BSc(hons) in Molecular Biology (2.1) from the University of Newcastle upon Tyne and I completed a Masters degree in Bioinformatics (distinction) at the University of Manchester in September 2007, shortly before I began my PhD.

Besides life sciences my interests include cycling, fishing, cooking (eating) and playing squash and the guitar.

The HIV retrovirus is the cause of the most destructive pandemic in recorded history. To understand and combat HIV, many research projects have accumulated extensive HIV-Human protein-protein interaction (PPI) data. PPI networks allow data from varied sources to be compiled such that entire systems can be studied and subject to further computational analyses. During the course of my PhD, I intend to build useful computational tools for investigating the Human-HIV1 PPI network and develop methods that can be applied to other host-pathogen networks.

My recent work, published in Plos Computational Biology, identifies significant host cellular subsystems that are perturbed during the course of HIV infection through specific patterns of virus-host interaction. This work provides an accessible and interpretable map of infection from a complex set of protein interactions.

Interaction networks can be studied to gain a greater understanding of the biological system that they represent. A common method for studying PPI networks is through visualization, typically by representing a network as a `ball-and-stick' graph. Interactive visualizations can enhance our understanding of networks and allow new patterns and trends to be discerned, particularly when these tools offer network analysis capabilities. However, most published PPI network visualizations are static representations that do not permit the user to view associated annotation let alone integrate and analyze other biological information in a useful manner. My first project was to develop a software package that could be used to render an interactive visualisation of the HIV-human protein interaction network. For this purpose JNets was developed.

JNets is a network visualization tool that incorporates annotation to explore the underlying features of interaction networks. The software is available as an application and a configurable applet that can provide a flexible and dynamic online interface to many types of network data. JNets was published in BMC Bioinformatics 2009, 10:95 (see below).