Author

Daniel Brady

University of SheffieldORCID 0000-0003-4671-0676Unclaimed 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 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Assay:electronic health records· 1 Organism:human· 1 Assay:imaging· 1 Approach:statistical model· 1

Frequent Co-Authors

Alice L. B. PyneiD· 1 shared Bertram OpitziD· 1 shared Hayley C. LeonardiD· 1 shared Laura WigginsiD· 1 shared Max C. GamilliD· 1 shared Neil ShephardiD· 1 shared Sylvia WhittleiD· 1 shared Thomas E. CatleyiD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperBiophysics

Alice L. B. PyneORCID

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2 papers

Recent·Most cited

BiophysicsComputational and Structural Biotechnology JournalPeer-reviewedMar 1, 2026

Deep Learning-Enhanced TopoStats for the Automated Quantification of DNA and Complex Biomolecular Structures

Sylvia Whittle, Tobias A Firth, Max C. Gamill…·Alice L. B. Pyne

The paper introduces an enhanced TopoStats tool using deep learning to automate and quantify AFM data, enabling detailed structural analysis of biomolecules.

DOI 10.34133/csbj.0227

imagingdeep learning

𝕏 PostBluesky

NeurosciencePLoS ONEPeer-reviewedNov 9, 2020

Motor and non-motor sequence prediction is equally affected in children with Developmental Coordination Disorder

Bertram Opitz, Daniel Brady, Hayley C. Leonard

This study investigates sequence prediction abilities in children with Developmental Coordination Disorder (DCD) across multiple domains, finding impaired explicit sequence discrimination but not implicit motor performance.

10 citations

humanelectronic health records

𝕏 PostBluesky