Innovation and Professional Development; School of Arts, Media and Computer Games: Taught to the MProf in Computer Games Development this module requires students to develop an innovative solution to an identifiable problem that sits beyond their current expertise. The student cohort is a mix of disciplines, including technology, art, design and sound production. Students must work in the face of an uncertain programme of research and development. Students are required to reflect on their development and how it has contributed to their professional practice.
Research Methods; Graduate School: Research Methods is a University-wide module delivered to all our post-graduate taught students. The module develops literature review skills, proposal writing and statistics at Masters level. The module draws on experts from across Abertay to provide insight into the nature of research at Masters level and to guide the production of a research proposal. For statistics teaching, the approach used is problem-led and the module instils in students how to select the right statistics in a given context.
Advanced Systems Biology in Biomedicine; School of Science, Engineering and Technology: Taught to Honours students on the BSc (Hons) Biomedical Science and BSc (Hons) Applied Biomedical Science, this module provides an integrative perspective on the role of systems biology and underpinning experimental systems in understanding and managing diseases, with a particular focus on cancer. Systems biology offers both a conceptual and a technical framework for integrating diverse, multi-scale, multi-stream data in bioscience generally.
My research explores the role of systems biology in understanding cancer. Cancer is a disease characterised by functional dysregulations within and surrounding affected cells, tissues and organs. These dysregulations confer cancerous cells with the ability to, among other features, proliferate at an increased rate, evade death and spread through the body. Cell behaviour is governed by a complex network of signalling regulatory pathways that ultimately dictate the development, maintenance and progression of the cancer as well as its histological and anatomical presentation and organisation. Anti-cancer drugs typically target key elements of this pathway in order to control these dysregulations, by either restoring normal functioning or blocking aberrant behaviour.
A major challenge in cancer therapy is drug resistance, which has at least two root causes. First, evolutionary mutations in cells can mean that the signalling network changes its function and the drugs lose efficacy. Second, the inherent heterogeneity of cells within a tumour combined with the specificity of the anti-cancer drugs means that a given therapy is likely to only target a sub-population of the cells in a tumour. Clearly to address this, we need to understand cellular signalling, tumour morphology and how each drives the other.
My research in cancer systems biology seeks to link cellular signalling and tumour morphology, and this requires a mix of complex systems modelling and agent-based modelling (EPSRC funded CoSMoS project), theoretical ecology in plant and fungal ecosystems, emergent behaviour in multi-agent robotic communities (EPSRC funded Artificial Cultures project) and interactive and dynamic visualisation of complex data. These areas of expertise combine to provide a unique approach to studying cancer based on the following research strands:
Bottom-up – Modelling the single cell. We have developed models of the cellular signalling pathways and their mechanistic responses to drug action. This allows us to explore the effects of cellular mutations on anti-cancer drug resistance (e.g. pdf), to unravel the regulatory mechanisms governing complex signalling dynamics (e.g. pdf) and to design combination therapies (e.g. pdf). Coupled to an innovative technology for dynamic and interactive visualisation of cell signalling dynamics we have developed an in silico drug discovery platform.
Top-down – Modelling the tumour. Tumour morphology may be studied in two dimensions, through imaging to show cross-sectional morphology or stained 2D-sections to revealing inner structures, or three dimensions to study whole tumour (surface) morphology. We have applied statistics developed in soil science to the study of 3D tumours. We have studied quantitatively the morphological response of tumours to therapeutic intervention (pdf).
Linking scales – Multi-cell modelling. In emerging work, we are developing a computational framework where individual cells, with potentially unique intra-cellular signalling networks, are able to interact in physical space. This framework will enable us to study heterogeneous populations of cells and how they interact to form emergent (tissue) structures.
Visiting Fellow, Department of Computer Science, University of York, 2011-
External examiner, Media School, Bournemouth University, 2011-
QAA Scotland Enhancement Theme for Research-Teaching linkages. Institutional Contact, 2007