| Mean-field models for non-Markovian epidemics on networks N Sherborne, JC Miller, KB Blyuss, IZ Kiss Journal of mathematical biology 76, 755-778, 2018 | 59 | 2018 |
| Sublethal effect modelling for environmental risk assessment of chemicals: Problem definition, model variants, application and challenges N Sherborne, N Galic, R Ashauer Science of the Total Environment 745, 141027, 2020 | 28 | 2020 |
| Dynamics of multi-stage infections on networks N Sherborne, KB Blyuss, IZ Kiss Bulletin of mathematical biology 77, 1909-1933, 2015 | 28 | 2015 |
| Modeling sublethal effects of chemicals: application of a simplified dynamic energy budget model to standard ecotoxicity data N Sherborne, N Galic Environmental Science & Technology 54 (12), 7420-7429, 2020 | 13 | 2020 |
| Bursting endemic bubbles in an adaptive network N Sherborne, KB Blyuss, IZ Kiss Physical Review E 97 (4), 042306, 2018 | 9 | 2018 |
| Compact pairwise models for epidemics with multiple infectious stages on degree heterogeneous and clustered networks N Sherborne, KB Blyuss, IZ Kiss Journal of Theoretical Biology 407, 387-400, 2016 | 9 | 2016 |
| Mean-field models for non-Markovian epidemics on networks: from edge-based compartmental to pairwise models N Sherborne, JC Miller, KB Blyuss, IZ Kiss arXiv preprint arXiv:1611.04030, 2016 | 7 | 2016 |
| Considerations for using reproduction data in toxicokinetic–toxicodynamic modeling T Jager, M Trijau, N Sherborne, B Goussen, R Ashauer Integrated Environmental Assessment and Management 18 (2), 479-487, 2022 | 6 | 2022 |
| The application and limitations of exposure multiplication factors in sublethal effect modelling N Sherborne, T Jager, B Goussen, M Trijau, R Ashauer Scientific Reports 12 (1), 6031, 2022 | 2 | 2022 |
| Non-Markovian Epidemic Dynamics on Networks N Sherborne University of Sussex, 2018 | | 2018 |
