Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Quantitative SARS-CoV-2 anti-spike responses to Pfizer–BioNTech and Oxford–AstraZeneca vaccines by previous infection status

Eyre DW. et al, (2021), Clinical Microbiology and Infection, 27, 1516.e7 - 1516.e14

Genomic network analysis of environmental and livestock F-type plasmid populations

Matlock W. et al, (2021), The ISME Journal, 15, 2322 - 2335

GenomegaMap: Within-Species Genome-Wide dN/dS Estimation from over 10,000 Genomes

Wilson DJ. et al, (2020), Molecular Biology and Evolution, 37, 2450 - 2460

Application of machine learning techniques to tuberculosis drug resistance analysis

Kouchaki S. et al, (2019), Bioinformatics, 35, 2276 - 2282

Scalable Pathogen Pipeline Platform (SP^3): Enabling Unified Genomic Data Analysis with Elastic Cloud Computing

Yang-Turner F. et al, (2019), 2019 IEEE 12th International Conference on Cloud Computing (CLOUD)

Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing

(2018), New England Journal of Medicine, 379, 1403 - 1415

The Human Scavenger Receptor CD36

Hoosdally SJ. et al, (2009), Journal of Biological Chemistry, 284, 16277 - 16288