Author

Michael P. Philpott

Queen Mary University of LondonORCID 0000-0002-1255-4612Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Cancer Biology· 1 Cell Biology· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 3 Research Focus:differential expression· 3 Organism:human· 3 Assay:scRNA-seq· 2 Research Focus:cell-cell communication· 1 Approach:experimental assay· 1 Research Focus:host-pathogen & immune response· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Abish S. StepheniD· 1 shared Adrian BiddleiD· 1 shared Andrew E. M. DavisiD· 1 shared Bethany K. HughesiD· 1 shared Claire PardieuiD· 1 shared Cleo L. BishopiD· 1 shared Dania Zuhier Ragheb AlkhatibiD· 1 shared David Andrew GunniD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 14 mutual co-author links

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1 shared paperMicrobiology

Abish S. StephenORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

Cancer BiologybioRxivPreprintOct 12, 2026

Malignant and stromal partial EMT programmes and cetuximab outcome in head and neck cancer

Dania Zuhier Ragheb Alkhatib, Sophia Lunetto, Priyanka Chakraborty…·Namshik Han

The paper identifies malignant and stromal partial EMT programs in head and neck cancer and shows that malignant measures correlate with better cetuximab outcomes.

DOI 10.64898/2026.10.09.757840

humanscRNA-seq

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MicrobiologybioRxivPreprintJul 1, 2025

Microbially-competent skin organotypics reveal dysregulated AhR signalling in microbial dysbiosis

E. McPolin-Hall, Abish S. Stephen, Claire Pardieu…·Rosalind F. Hannen

This study uses 3D skin organotypics to show that microbial dysbiosis disrupts AhR signaling, contributing to dandruff pathogenesis.

DOI 10.1101/2025.07.01.662505

humanspatial transcriptomics

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Cell BiologybioRxivPreprintOct 23, 2023

SenPred: A single-cell RNA sequencing-based machine learning pipeline to classify senescent cells for the detection of an in vivo senescent cell burden

Bethany K. Hughes, Andrew E. M. Davis, Deborah Milligan…·Cleo L. Bishop

SenPred uses scRNA-seq to classify senescent cells and detects in vivo senescent cell burden with high accuracy.

5 citations

humanscRNA-seq

𝕏 PostBluesky