Methods for Protein Structure Analysis by Electron Paramagnetic Resonance. This highly interdisciplinary project aims to establish new tools to analyse the structure and motions of proteins that are otherwise difficult to study. A combination of advanced biochemistry, modern magnetic spectroscopy methods, and high-performance computing techniques will be applied to study proteins at physiological concentrations and in complex environments. New techniques will be developed and tested on proteins ....Methods for Protein Structure Analysis by Electron Paramagnetic Resonance. This highly interdisciplinary project aims to establish new tools to analyse the structure and motions of proteins that are otherwise difficult to study. A combination of advanced biochemistry, modern magnetic spectroscopy methods, and high-performance computing techniques will be applied to study proteins at physiological concentrations and in complex environments. New techniques will be developed and tested on proteins of high biochemical or biomedical importance, and the approach will be applied to established drug targets.Read moreRead less
Decoding miRNA regulated genetic circuits. This project will aim to develop a much better understanding of how the process of making proteins from genes is regulated, and will develop scientific software capable of predicting how a cell will respond to changes in this regulation. The results will have widespread use, including assistance in deciding the best treatments for genetic diseases.
Developing bioinformatics methods for single cell transcriptomics. This project aims to develop novel bioinformatics methods for single cell transcriptomic data that seek to model variability in cell populations. The project expects to generate new approaches using Bayesian statistics that will act as high-end enablers of discovery in transcriptional regulatory processes. Through an interdisciplinary combination of experimental and computational research, insights into fundamental biological pro ....Developing bioinformatics methods for single cell transcriptomics. This project aims to develop novel bioinformatics methods for single cell transcriptomic data that seek to model variability in cell populations. The project expects to generate new approaches using Bayesian statistics that will act as high-end enablers of discovery in transcriptional regulatory processes. Through an interdisciplinary combination of experimental and computational research, insights into fundamental biological processes will be elucidated, specifically the robustness of cellular systems. Expected outcomes include a suite of novel tools that will push the boundaries of current bioinformatics solutions with potential to deliver significant benefits to every domain of biological science, particularly tissue engineering and synthetic biology.Read moreRead less