Professor SIMON PRESTON's Outputs (2)

Empirical Quantification of Predictive Uncertainty Due to Model Discrepancy by Training with an Ensemble of Experimental Designs: An Application to Ion Channel Kinetics (2023)
Journal Article
Shuttleworth, J. G., Lei, C. L., Whittaker, D. G., Windley, M. J., Hill, A. P., Preston, S. P., & Mirams, G. R. (2024). Empirical Quantification of Predictive Uncertainty Due to Model Discrepancy by Training with an Ensemble of Experimental Designs: An Application to Ion Channel Kinetics. Bulletin of Mathematical Biology, 86(1), Article 2. https://doi.org/10.1007/s11538-023-01224-6

When using mathematical models to make quantitative predictions for clinical or industrial use, it is important that predictions come with a reliable estimate of their accuracy (uncertainty quantification). Because models of complex biological system... Read More about Empirical Quantification of Predictive Uncertainty Due to Model Discrepancy by Training with an Ensemble of Experimental Designs: An Application to Ion Channel Kinetics.

Using many different voltage protocols to characterise discrepancy in mathematical ion channel models (2023)
Journal Article
Shuttleworth, J. G., Lok Lei, C., Windley, M., Hill, A. P., Perry, M. D., Preston, S., & Mirams, G. R. (2023). Using many different voltage protocols to characterise discrepancy in mathematical ion channel models. Biophysical Journal, 122(3, Suppl. 1), 242a. https://doi.org/10.1016/j.bpj.2022.11.1415

The Kv11.1 protein encoded by the hERG gene forms the primary subunit of a voltage-sensitive ion channel responsible for IKr in cardiomyocytes. Mathematical models of the macroscopic current are fitted to data from patch-clamp experiments - in which... Read More about Using many different voltage protocols to characterise discrepancy in mathematical ion channel models.