Author

Joseph G. Shuttleworth

University of NottinghamORCID 0000-0003-4884-6526Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Organism:Arabidopsis· 1 Research Focus:benchmarking· 1 Assay:electrophysiology· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Adam Parker HilliD· 1 shared Anthony BishoppiD· 1 shared Chon Lok LeiiD· 1 shared Emily ChaniD· 1 shared Etienne FarcotiD· 1 shared Gary R. MiramsiD· 1 shared Monique J. WindleyiD· 1 shared Rahul BhosaleiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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1 shared paperBiophysics

Adam Parker HillORCID

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2 papers

Recent·Most cited

Plant BiologybioRxivPreprintSep 5, 2026

A general mathematical framework for modelling subnetworks of the nuclear auxin pathway

Joseph G. Shuttleworth, Emily Chan, Thomas Welch…·Etienne Farcot

The paper presents a general ODE-based framework to model subnetworks of the nuclear auxin pathway and demonstrates its application to Arabidopsis thaliana root data.

DOI 10.64898/2026.08.06.742982

Arabidopsisstatistical model

𝕏 PostBluesky

BiophysicsPhilosophical Transactions of the Royal Society A Mathematical Physical and Engineering SciencesPeer-reviewedMar 13, 2025

Evaluating the predictive accuracy of ion channel models using data from multiple experimental designs

Joseph G. Shuttleworth, Chon Lok Lei, Monique J. Windley…·Gary R. Mirams

The paper evaluates the predictive accuracy of IKr ion channel models using voltage-clamp data from multiple experimental protocols and identifies parameter heterogeneity across cells.

3 citations

electrophysiologystatistical model

𝕏 PostBluesky