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

Publications by Computational Biology and Bioinformatics

Hillis, S. et al. (2021) “Global minimum estimates of children affected by COVID-19-associated orphanhood and deaths of caregivers: a modelling study.”, Lancet (London, England), 398(10298), pp. 391–402.

Knock, E. et al. (2021) “Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England”, Science Translational Medicine, 13(602).

Charniga, K. et al. (2021) “Descriptive analysis of surveillance data for Zika virus disease and Zika virus-associated neurological complications in Colombia, 2015–2017”, PLoS ONE, 16(6).

Speidel, L. et al. (2021) “Inferring population histories for ancient genomes using genome-wide genealogies”, Molecular Biology and Evolution, 38(9), pp. 3497–3511.

He, Y., Reinert, G. and Cucuringu, M. (2021) “DIGRAC: Digraph Clustering Based on Flow Imbalance”, in.

Marks, C. et al. (2021) “Identifying counties at risk of high overdose mortality burden throughout the emerging fentanyl epidemic in the United States: a predictive statistical modeling study”, Lancet Public Health, 6(10), pp. e720 - e728.

Parag, K., Thompson, R. and Donnelly, C. (2021) “Are epidemic growth rates more informative than reproduction numbers?”, medRxiv [Preprint].

Davies, R. et al. (2021) “Rapid genotype imputation from sequence with reference panels”, Nature Genetics, 53(7), pp. 1104–1111.

Lovell-Read, F. et al. (2021) “Interventions targeting non-symptomatic cases can be important to prevent local outbreaks: SARS-CoV-2 as a case study”, Journal of the Royal Society Interface, 18(178).

Klimm, F., Deane, C. and Reinert, G. (2021) “Hypergraphs for predicting essential genes using multiprotein complex data”, Journal of Complex Networks, 9(2).