Understanding influenza virus evolution and adaptation through natural language processing
Supervisors:
Edward Hutchinson, Glasgow Centre for Virus Research, School of Infection and Immunity, (University of Glasgow)
Derek Gatherer, Biomedical & Life Sciences, (Lancaster University)
Joseph Hughes, Glasgow Centre for Virus Research, School of Infection and Immunity, (University of Glasgow)
Summary:
Leveraging natural language processing (NLP) and artificial intelligence (AI) for viral mutation analysis in influenza
This PhD project offers an exciting opportunity to apply advanced natural language processing techniques to a critical area of virology. The focus is on automating the extraction and analysis of viral genetic variations, particularly in influenza, from vast scientific literature. Understanding the functional significance of mutations related to virulence, host adaptation, and drug resistance is key to staying ahead of rapidly evolving viruses. By integrating viral evolution data with the functional and structural impacts of mutations, this research will enhance our ability to respond to emerging viral threats. Although the primary focus is on influenza, the tools and methodologies developed will be applicable across a broader range of viruses, making this project highly impactful for virology research and public health.
The student will gain hands-on experience with cutting-edge NLP artificial intelligence techniques, including large language models, text mining, named entity recognition, and relation extraction. The project provides practical training in biomedical informatics, with a focus on genomic and molecular data analysis. Working alongside experts in virology, machine learning, and bioinformatics, students will develop interdisciplinary communication skills and gain invaluable insights into computational approaches to virology, with the option of developing molecular virology skills to test their predictions experimentally. This is a unique opportunity for those interested in applying machine learning to solve critical challenges in viral research.