Author

Ian Halliday

Insigneo

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Systems Biology· 2 Bioengineering· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:cell type annotation· 1 Organism:human· 1 Assay:imaging· 1 Research Focus:variant calling· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Harry SaxtoniD· 2 shared Richard H. ClaytoniD· 2 shared Torsten SchenkeliD· 2 shared Xu XuiD· 2 shared Andrew James NarracottiD· 1 shared Chung Sim LimiD· 1 shared Daniel J. Taylor· 1 shared Grace FaulkneriD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersSystems Biology

Harry SaxtonORCID

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Author profile →

3 papers

Recent·Most cited

Iliac vein morphology and wall shear stress: a statistical shape modelling and CFD analysis of patient-specific geometries

Magdalena Otta, Karol Zając, Ian Halliday, Chung Sim Lim, Maciej Malawski, Andrew James Narracott

This study compares how different levels of anatomical detail in venous models affect haemodynamic risk metrics using statistical shape modelling and CFD.

bioRxiv · Feb 18, 2026 · PreprintBioengineering

THE IMPACT OF EXPERIMENTAL DESIGNS & SYSTEM SLOPPINESS ON THE PERSONALISATION PROCESS: A CARDIOVASCULAR PERSPECTIVE

Harry Saxton, Daniel J. Taylor, Grace Faulkner, Ian Halliday, Tom Newman, Torsten Schenkel, Paul Morris, Richard H. Clayton, Xu Xu

This paper quantifies cardiovascular system sloppiness and shows how experimental design impacts model personalisation, revealing continuous measurements increase biomarkers but also sloppiness.

PLoS ONE · Jun 24, 2025Peer-reviewedSystems Biology

CONVERGENCE, SAMPLING AND TOTAL ORDER ESTIMATOR EFFECTS ON PARAMETER ORTHOGONALITY IN GLOBAL SENSITIVITY ANALYSIS

Harry Saxton, Xu Xu, Torsten Schenkel, Richard H. Clayton, Ian Halliday

This paper evaluates total-order estimators and sampling methods in global sensitivity analysis, finding that Jansen and Janon estimators with Sobol and lattice rule sampling provide efficient convergence for parameter orthogonality.

PLoS Computational Biology · Jul 17, 2024Peer-reviewedSystems Biology