- Dynamic Simulation Modelling
- Parameter Estimation for Biological Models
- Stochastic Modelling in Systems Biology
- Biological Image Analysis
- High-throughput, robotic screens
I am a mathematical biologist and I work as a research scientist in the Lydall lab
which is part of the the Institute for Cellular & Molecular Biosciences at Newcastle University. I have quite a wide range of interests, but currently I work on cell-population studies of ageing phenotypes (e.g. cellular senescence and growth defects in response to telomere uncapping and DNA damage). I use and develop computational and mathematical tools to describe and predict the growth of model biological systems such as cultured yeast and human cell lines.
I have developed a wide range of computational tools for genome-wide screening of microbial cultures which are used successfully in the lab and in Newcastle University's high-throughput screening facility bioHT.
- BASIS - Stochastic simulation & storage of SBML models for ageing research. Now defunct due to lack of funding.
- CaliBayes - Bayesian parameter inference for stochastic simulations of SBML models. Now defunct due to lack of funding.
- Colonyzer - Robust image analysis tool for estimating cell density in arrayed microbial cultures growing on agar plates.
- qfaR - Comprehensive R package for carrying out Quantitative Fitness Analysis (QFA). Tracks individual cultures in timelapse images,
constructs growth curves, fits growth models estimates fitnesses and infers the presence of genetic interactions. Also contains several tools for visualisation of QFA data.
- qfaViz - Online tool for visualisation of QFA datasets.
- senesceR - Stochastic simulations of cell populations undergoing transition from proliferation competence to replicative senescence.
I run a short, introductory course on Python for postgraduate students in Newcastle University medical school.
The course materials are freely available here.
My publication list can be found on a separate page here.
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Last updated: November 2012