Author

Rufus H. Daw

Manchester Academic Health Science CentreORCID 0000-0003-1258-937XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:experimental assay· 2 Assay:scRNA-seq· 2 Approach:deep learning· 1 Research Focus:gene regulatory network inference· 1 Organism:mouse· 1 Research Focus:spatial domain detection· 1 Approach:statistical model· 1

Frequent Co-Authors

John R. GraingeriD· 2 shared Alfie SandersoniD· 1 shared Antony D. AdamsoniD· 1 shared Barry W. McColliD· 1 shared Charlotte L. ScottiD· 1 shared Chengcan YaoiD· 1 shared Christine ChewiD· 1 shared Christopher J. AndersoniD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersImmunology

John R. GraingerORCID

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2 papers

Recent·Most cited

ImmunologyThe Journal of Experimental MedicinePeer-reviewedMar 5, 2026

CD163 and Tim-4 identify resident intestinal macrophages across sub-tissular regions that are spatially regulated by TGF-β

V. Jayaraman, Ian E. Prise, Verena Kästele…·Tovah N. Shaw

The paper identifies CD163 and Tim-4 as markers for intestinal macrophages and shows TGF-β regulates their spatial distribution in different niches.

15 citationstop 1%

𝕏 PostBluesky

BioinformaticsbioRxivPreprintMar 5, 2026

CellTypeAI: Automated cell identification for scRNA-seq using local generative-AI

Rufus H. Daw, Harry R. Deijnen, Magnus Rattray, John R. Grainger

CellTypeAI improves scRNA-seq cell type annotation by using local generative-AI models, outperforming conventional and cloud-based methods in accuracy and sensitivity.

DOI 10.64898/2026.03.03.709253

scRNA-seqdeep learning

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