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]

Collection description

The dataset contains the raw data underpinning some of the figures in the research article. In addition, files needed to use algorithm necessary to identify alveolar epithelial hyperproliferation using the HALO software.

Funding:	Wellcome Trust (WELLCOTR) [206369/Z/17/Z]
College / School:	College of Medical Veterinary and Life Sciences > School of Infection and Immunity > Centre for Virus Research
Date Deposited:	18 Oct 2023 14:18
Related resources:	https://doi.org/10.1101/2023.08.01.551417 [Preprint]
URI:	https://researchdata.gla.ac.uk/id/eprint/1513
Additional details Additional details Type of data: Image, Spreadsheet, Text Collection period: From To January 2021 October 2023 Date: 18 October 2023 Date type: Publication Additional information: Funding acknowledged from: Medical Research Council (MC_UU_00034/5 and MC_UU_00034/9), UKRI (MR/W005611/1), and LifeArc COVID19 grant. Resource language: EN Status: Published Data Publisher: University of Glasgow Copyright holders: University of Glasgow Last Modified: 11 Apr 2024 11:41

Available Files

Data

Final_Raw_Data.zip Final_Raw_Data.zip Final_Raw_Data.zip Visible to: Anyone File size: 133MB License: CC BY-NC-SA 4.0

Read me

Readme.docx Readme.docx Readme.docx Visible to: Anyone File size: 13kB License: CC BY 4.0

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