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Maria Kiourlappou1 , Peter Todd1, Yaxuan Kong2, Jayesh Hire1 , Martin Sergeant3, Stefan Zohren2, Jim Hughes3, Stephen Taylor1 (1Centre of Human Genetics, University of Oxford, 2Department of Engineering, University of Oxford, 3Weatherall Institute of Molecular Medicine, University of Oxford)
Multi-Dimensional Viewer (MDV) is a tool for visualising genomics, transcriptomics, proteomics, and epigenetics datasets. Its user-friendly interface enables clinicians and scientists to explore, present, and share their analyses through interactive data visualisations. Effective integration and seamless analysis of these diverse, multi-modal and large biological datasets are crucial for advancing our understanding of human diseases, uncovering disease mechanisms, identifying new biomarkers, and discovering novel drug targets. To further enhance MDV's capabilities, we aim to empower users with little or no programming experience to analyse and visualise their data directly through natural language quering. Additionally, we strive to minimise the overhead required generating the views programmatically by automating the generation of visualisations using natural language. We present ChatMDV, an extension of MDV powered by Large Language Models (LLMs), which combines the flexibility of natural language input with MDV’s graphical point-and-click interface, enhancing both usability and functionality.