The University of Glasgow uses cookies for analytics. Find out more about our Privacy policy.
Necessary cookies enable core functionality. The website cannot function properly without these cookies, and can only be disabled by changing your browser preferences.
Analytical cookies help us improve our website. We use Google Analytics. All data is anonymised.
Hotjar and Clarity help us to understand our users’ behaviour by visually representing their clicks, taps and scrolling. All data is anonymised.
email:
Charalampos.Attipa@glasgow.ac.uk
Sir Graeme Davies Building, 120 University Avenue, Glasgow, G12 8TA
Meehan, G. R. et al. (2023) Phenotyping the virulence of SARS-CoV-2 variants in hamsters by digital pathology and machine learning. PLoS Pathogens, 19(11), e1011589. (doi: 10.1371/journal.ppat.1011589) (PMID:37934791) (PMCID:PMC10656012)
Meehan, G. R. et al. (2023) Phenotyping the virulence of SARS-CoV-2 variants in hamsters by digital pathology and machine learning. PLoS Pathogens, 19(11), e1011589. (doi: 10.1371/journal.ppat.1011589) (PMID:37934791) (PMCID:PMC10656012)
Meehan, G. , Herder, V. , Allan, J., Huang, X., Kerr, K., Correa Mendonca, D. , Ilia, G., Wright, D. , Nomikou, K., Gu, Q. , Molina Arias, S., Hansmann, F., Hardas, A., Attipa, C., De Lorenzo, G. , Cowton, V., Upfold, N. , Palmalux, N., Brown, J., Barclay, W., Da Silva Filipe, A. , Furnon, W. , Patel, A. and Palmarini, M. (2023) Phenotyping the virulence of SARS-CoV-2 variants in hamsters by digital pathology and machine learning. [Data Collection]