Publications (Computational Biology and Bioinformatics) | Department of Statistics

Publications by Computational Biology and Bioinformatics

He, Y. et al. (2022) “GNNRank: learning global rankings from pairwise comparisons via directed graph neural networks”, in Proceedings of the 39th International Conference on Machine Learning. Journal of Machine Learning Research, pp. 8581–8612.

Chadeau-Hyam, M. et al. (2022) “Omicron SARS-CoV-2 epidemic in England during February 2022: A series of cross-sectional community surveys.”, The Lancet regional health. Europe, 21, p. 100462.

Lu, Y., Reinert, G. and Cucuringu, M. (2022) “Trade co-occurrence, trade flow decomposition, and conditional order imbalance in equity markets.”

Fischer, A. et al. (2022) “Normal approximation for the posterior in exponential families.”

Menkir, T. and Donnelly, C. (2022) “The impact of repeated rapid test strategies on the effectiveness of at-home antiviral treatments for SARS-CoV-2”, Nature Communications, 13(1), pp. 5283–5283.

Mullins, E. et al. (2022) “Tracking the incidence and risk factors for SARS-CoV-2 infection using historical maternal booking serum samples”, PLoS ONE, 17(9).

Ezanno, P. et al. (2022) “The African swine fever modelling challenge: Model comparison and lessons learnt”, Epidemics, 40, p. 100615.

Parag, K., Donnelly, C. and Zarebski, A. (2022) “Quantifying the information in noisy epidemic curves”, Nature Computational Science, 2(9), pp. 584–594.

Eales, O. et al. (2022) “Appropriately smoothing prevalence data to inform estimates of growth rate and reproduction number”, Epidemics, 40, p. 100604.

Dankwa, E. et al. (2022) “Stochastic modelling of African swine fever in wild boar and domestic pigs: epidemic forecasting and comparison of disease management strategies”, Epidemics, 40.