Publications (Computational Biology and Bioinformatics) | Department of Statistics - University of Oxford

Publications by Computational Biology and Bioinformatics

Cooper, J. et al. (2022) “Topological analysis of credit data: preliminary findings”, in Proceedings of the 23rd International Conference on Intelligent Data Engineering and Automated Learning (IDEAL). Springer, pp. 432–442.

Parag, K., Thompson, R. and Donnelly, C. (2022) “Authors’ reply to the discussion of ‘Are epidemic growth rates more informative than reproduction numbers?’ by Parag et al. in Session 1 of the Royal Statistical Society’s Special Topic Meeting on COVID-19 Transmission: 9 June 2021”, Journal of the Royal Statistical Society: Statistics in Society Series A, 185(S1), pp. S55 - S60.

Whitaker, M. et al. (2022) “Variant-specific symptoms of COVID-19 in a study of 1,542,510 adults in England”, Nature Communications, 13.

Bennett, S., Cucuringu, M. and Reinert, G. (2022) “Lead–lag detection and network clustering for multivariate time series with an application to the US equity market”, Machine Learning, 111(12), pp. 4497–4538.

Anastasiou, A. et al. (2022) “Stein’s method meets computational statistics: a review of some recent developments”, Statistical Science, 38(1), pp. 120–139.

Fathi, M. et al. (2022) “Relaxing the Gaussian assumption in shrinkage and SURE in high dimension”, Annals of Statistics, 50(5), pp. 2737–2766.

Dankwa, E., Brouwer, A. and Donnelly, C. (2022) “Structural identifiability of compartmental models for infectious disease transmission is influenced by data type”, Epidemics, 41.

Weckbecker, M., Xu, W. and Reinert, G. (2022) “On RKHS choices for assessing graph generators via kernel Stein statistics.”

Unwin, H. et al. (2022) “Using next generation matrices to estimate the proportion of infections that are not detected in an outbreak”, Epidemics, 41.

Limnios, S. et al. (2022) “Random walk based conditional generative model for temporal networks with attributes”, in Advances in Neural Information Processing Systems 36 (NeurIPS 2022). Neural Information Processing Systems Foundation.