Author

Sam T. M. Ball

University of LiverpoolORCID 0000-0001-5347-8647Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Approach:diffusion model· 1 Assay:electronic health records· 1 Assay:imaging· 1 Organism:mouse· 1

Frequent Co-Authors

D. WilkinsoniD· 1 shared David A. TurneriD· 1 shared Kai F. HoettgesiD· 1 shared Meagan J. Hennessy· 1 shared Michael WhiteiD· 1 shared Neil D. PerkinsiD· 1 shared Richard Barrett‐JolleyiD· 1 shared Yalin ZhengiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 28 mutual co-author links

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1 shared paperBioinformatics

D. WilkinsonORCID

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2 papers

Recent·Most cited

DiffuChannel: A Conditional Denoising Diffusion Model that Synthesises Single-Molecule Patch-Clamp Data with Exactly Known Idealisation (Ground Truth)

Samuel A. Ball, Richard Barrett‐Jolley

DiffuChannel generates synthetic single-molecule patch-clamp data with known idealisation using a conditional diffusion model, outperforming GAN-based methods in stability and realism.

bioRxiv · Oct 14, 2026 · PreprintBiophysics

Domain Specific AI Segmentation of IMPDH2 Rod/Ring Structures in Mouse Embryonic Stem Cells

Sam T. M. Ball, Meagan J. Hennessy, Yuhan Tan, Kai F. Hoettges, Neil D. Perkins, D. Wilkinson, Michael White, Yalin Zheng, David A. Turner

The paper develops an AI pipeline to automatically segment IMPDH2 rod-ring structures in mouse ESCs, achieving high accuracy and agreement with expert annotations.

BMC Biology · May 11, 2025Peer-reviewedBioinformatics