I work with large public and restricted access datasets in the human and avian omics fields and work closely with wet-lab colleagues to generate new, hypothesis-driven data. My research has benefited a lot from working with these data, but it’s not always straightforward. I want to help researchers across the life sciences benefit from these data as well, especially if they are wet-lab focused. I want to give researchers the skills to identify relevant datasets, ensure those data are suitable for their research or student supervision, and to better understand the requirements for managing a new cohort of sensitive data. As a proleptic lecturer, I am also very well-placed to introduce data management and FAIR concepts into biological undergraduate teaching and projects.
I am a Research Fellow and Proleptic Lecturer in Cancer Informatics in the Department of Biology and York Biomedical Research Institute at The University of York. I am the PI of a small, bioinformatics-focused research group, within a cancer unit funded by the local charity York Against Cancer. I am interested in genomic and transcriptomic dysregulation in diverse cancers. I mainly study urothelial carcinoma, including as a bioinformatic lead in the bladder cancer group of the Genomics England 100,000 Genomes Project. I am, however, interested in diverse cancers, including retroviral-induced disease in chickens, which follows on from my PhD and initial postdoctoral research. I supervise undergraduate, masters-level and PhD students, and work closely with wet lab-focused researchers in generating, storing and analysing high-throughput sequencing data from both short-read and long-read technologies. I am interested in training these predominantly wet-lab researchers to identify, QC and utilise existing public and restricted access datasets to enhance their specific areas of research.