Publications by Computational Biology and Bioinformatics Charniga, K. et al. (2021) “Spatial and temporal invasion dynamics of the 2014–2017 Zika and chikungunya epidemics in Colombia”, PLOS Computational Biology, 17(7), p. e1009174. 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. 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. He, Y., Reinert, G. and Cucuringu, M. (2021) “DIGRAC: Digraph Clustering Based on Flow Imbalance”, in. 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). Previous page ‹‹ … Page 26 Page 27 Page 28 Page 29 Current page 30 Page 31 Page 32 Page 33 Page 34 … Next page ››