Davies, Richard

Attributes and predictors of long COVID

Sudre, C. H., Murray, B., Varsavsky, T., Graham, M. S., Penfold, R. S., Bowyer, R. C., Pujol, J. C., Klaser, K., Antonelli, M., Canas, L. S., et al. (2021) · Nature Medicine

Long-Term Effects of COVID-19COVID-19 Clinical Research Studies

Cited by 2,707

Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4

Blanco-Míguez, A., Beghini, F., Cumbo, F., McIver, L. J., Thompson, K. N., Zolfo, M., Manghi, P., Dubois, L., Huang, K. D., Thomas, A. M., et al. (2023) · Nature Biotechnology

Genomics and Phylogenetic StudiesGut microbiota and health

Cited by 1,442

Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals

Asnicar, F., Berry, S. E., Valdes, A. M., Nguyen, L. H., Piccinno, G., Drew, D. A., Leeming, E., Gibson, R., Le Roy, C., Khatib, H. A., et al. (2021) · Nature Medicine

Gut microbiota and healthNutrition, Genetics, and Disease

Cited by 995

Human postprandial responses to food and potential for precision nutrition

Berry, S. E., Valdes, A. M., Drew, D. A., Asnicar, F., Mazidi, M., Wolf, J., Capdevila, J., Hadjigeorgiou, G., Davies, R., Al Khatib, H., et al. (2020) · Nature Medicine

Nutrition, Genetics, and DiseaseDiet, Metabolism, and Disease

Cited by 932

Gut microbiome signatures of vegan, vegetarian and omnivore diets and associated health outcomes across 21,561 individuals

Fackelmann, G., Manghi, P., Carlino, N., Heidrich, V., Piccinno, G., Ricci, L., Piperni, E., Arrè, A., Bakker, E., Creedon, A. C., et al. (2025) · Nature Microbiology

Gut microbiota and healthNutritional Studies and Diet

Cited by 142

Personalised REsponses to DIetary Composition Trial (PREDICT): an intervention study to determine inter-individual differences in postprandial response to foods

Berry, S., Drew, D., Linenberg, I., Wolf, J., Hadjigeorgiou, G., Davies, R., Khatib, H. A., Hart, D., Surdulescu, G., Yarand, D., et al. (2020)

Nutrition, Genetics, and DiseaseMetabolomics and Mass Spectrometry Studies

Cited by 33

Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app

Bowyer, R. C. E., Varsavsky, T., Thompson, E. J., Sudre, C. H., Murray, B. A. K., Freidin, M. B., Yarand, D., Ganesh, S., Capdevila, J., Bakker, E., et al. (2021) · Thorax

COVID-19 epidemiological studiesData-Driven Disease Surveillance

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