I originally studied Chemistry and Law at the University of Exeter intending on becoming a lawyer. Then I met some lawyers and decided I would be better of sticking with being a scientist. So instead I did a PhD in molecular modelling and protein crystallography also at Exeter. What drew me to this field was that it involved computers and the graphics looked amazing.
After finishing my PhD I became the post-doc. computer geek helping everyone with their analysis and generating all of their images. Luckily this had by then become an academic field of its own because of the growing need for using computation to analyse the biological data available from the genome projects. This field became known as bioinformatics or computational biology, depending on if the information or the modelling is more important to you as a researcher.
I helped start the MSc in Bioinformatics at Exeter and I taught there for 5 years until I moved to the University of Oxford to help run their Bioinformatics MSc, which I also did for 5 years. At Oxford Bioinformatics falls under the remit of Statistics and so I had to develop my statistics skills.
Now at Westminster I am responsible for teaching statistics and research skills, as well as continuing my research in bioinformatics/computational biology.
I have taught across the complete spectrum of courses within Bioinformatics. As my background was in sequence and structure analysis this was my starting point for teaching but I have also taught Perl programming, microarrays, Linux computing, proteomics, statistics and statistical data-mining.
I have taught introductory courses using R and SPSS for statistical analysis.
I currently teach on the Levels 5 and 7 Research Methods Modules the Level 6 and Level 5 Bioinformatics Modules, Bioinformatics in Medicine as well as supervising MSc and Undergraduate Projects.
I am the module leader for the level 6 and new level 5 Bioinformatics modules.
I am very interested in online and blended learning as some of the modules at Oxford were taught online. I am also interested in the idea of Gamification and using simulations and real problems as a basis for teaching.
I am currently working of a wide range of projects:
- The evolution of H9N2 hemagglutinin
- The use of word based methods to detect novel miRNAs
- A grammar of network models
- The evolution of fructose 1,6-bisphosphate aldolase
- Modeling protein unfolding in lysozyme and crambin
- Protein unfolding in nvCJD
- COPASAAR II (simple amino acid repeat database)
- Microbiome analysis (in collaboration with S. Moschos)
- Modeling diffusion processes using electronic circuits (in collaboration with ECS)
I work on applying computational modeling and analysis techniques to large-scale biological datasets. The aim is to incorporate many different levels of biological data to build better models, and improve our understanding.
Students will develop their analytical, statistical and computational skills and show that they can work with "Big Data". Visualisation and presentation is an important part of any project where there are large amounts of data and these are essential skills for a wide range of employers. Possible project areas are:
- Flu evolution
- Metabolic pathway evolution
- Protein misfolding diseases
- Sequence patterns in proteomes
- Diffusion based models of populations (individual based models)