Engineering Methods for Resolving Complex Mutational Networks in Proteins

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This project aims to develop a novel computational framework for resolving complex mutational networks that underpin how proteins function and evolve over time. It seeks to develop statistical inference methods that are robust, efficient, and widely applicable. The project will promote international collaboration and spawn multidisciplinary research by introducing parameter estimation and optimisation techniques that stem from signal processing, mobile wireless communications, and random matrix theory. The project's outputs can be used to understand diverse protein systems and have the potential to be applied to wide-ranging applications from protein engineering to brain signal analysis to vaccine design.