Advanced Topics in Quantitative Biology

Biological research techniques are changing rapidly, and each year we learn about new ways of collecting and analysing large biological datasets. New empirical data often require novel methods of analysis, and large datasets require advanced computational techniques to handle. Quantitative biologists also frequently rely on mathematical and simulation models to explore and understand complex biological processes and patterns. At the heart of quantitative biology is asking the right question, in the right way, with traditional experimental design during data collection being replaced by (i) decisions about how to partition existing datasets and (ii) parameter definitions in simulation models to effectively answer outstanding biological questions. Students will learn about advanced methods in quantitative biology, from study design, reading and writing skills, through to theory and agent-based modelling, mining citizen-science data, analysing of animal tracking data, and using deep-learning method.