Author

Daniel Harding

Queen Mary University of LondonORCID 0000-0002-7169-4252Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:benchmarking· 1 Research Focus:cell signaling & trafficking· 1 Research Focus:cell type annotation· 1 Assay:electronic health records· 1 Approach:experimental assay· 1 Assay:flow cytometry· 1 Research Focus:host-pathogen & immune response· 1

Frequent Co-Authors

Amaia Carrascal-MiniñoiD· 1 shared Anne Worthington· 1 shared Areti PapadopoulouiD· 1 shared Benny ChainiD· 1 shared Caroline Sutcliffe· 1 shared Conor Garrod-Ketchely· 1 shared Dina Tamsan· 1 shared Dunja AksentijevićiD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperImmunology

Amaia Carrascal-MiniñoORCID

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2 papers

Recent·Most cited

Characterisation of distinct senescent-like T cell populations during healthy and unhealthy ageing

Conor Garrod-Ketchely, Lauren A. Callender, Johannes Schroth, Katie Littlewood, Elizabeth C. Carroll, Dina Tamsan, Victoria Tsang, Isabell Nessel, Natalie E. Riddell, Benny Chain, Dunja Aksentijević, Daniel Harding, Federica M. Marelli‐Berg, Jonas Byström, Melissa Pereira Da Costa, , Siân M. Henson

This study identifies a distinct senescent-like CD8 TEMRA cell population in older individuals with type 2 diabetes, linked to metabolic inflammation and impaired immune function.

bioRxiv · Jun 16, 2025 · PreprintImmunology

Prediction of atrial fibrillation and stroke using machine learning models in UK Biobank.

Areti Papadopoulou, Daniel Harding, Greg Slabaugh, Eirini Marouli, Panos Deloukas

This paper uses machine learning to predict atrial fibrillation and ischemic stroke risk using UK Biobank data, finding LightGBM outperforms other models for AF and XGBoost for stroke.

Heliyon · Mar 16, 2024Peer-reviewedGenetic & Genomic Medicine