Publications by Computational Biology and Bioinformatics

Agarwal, I. et al. (2023) “Relating pathogenic loss-of-function mutations in humans to their evolutionary fitness costs”, eLife, 12, p. e83172.

Raybould, M. et al. (2023) “Computationally profiling peptide: MHC recognition by T-cell receptors and T-cell receptor-mimetic antibodies”, Frontiers in Immunology, 13.

McCabe, R. et al. (2023) “Alternative epidemic indicators for COVID-19: a model-based assessment of COVID-19 mortality ascertainment in three settings with incomplete death registration systems”, medRxiv.

Spoendlin, F. et al. (2023) “Improved computational epitope profiling using structural models identifies a broader diversity of antibodies that bind the same epitope”, bioRxiv.

Watson, L. et al. (2023) “Improving estimates of epidemiological quantities by combining reported cases with wastewater data: a statistical framework with applications to COVID-19 in Aotearoa New Zealand”, medRxiv.

Atchison, C. et al. (2023) “LONG-TERM PHYSICAL AND MENTAL HEALTH IMPACT OF COVID-19 ON ADULTS IN ENGLAND: FOLLOW UP OF A LARGE RANDOM COMMUNITY SAMPLE”, medRxiv.

Mijoule, G. et al. (2023) “Stein’s density method for multivariate continuous distributions”, Electronic Journal of Probability, 28(none).

Penn, M. et al. (2023) “The uncertainty of infectious disease outbreaks is underestimated”, Research Square.

He, Y. et al. (2023) “PyTorch Geometric Signed Directed: A Software Package on Graph Neural Networks for Signed and Directed Graphs”, in Proceedings of Machine Learning Research, pp. 121–1227.

Mills, C. et al. (2023) “Strategic use of SARS-CoV-2 wastewater concentration data could enhance, but not replace, high-resolution community prevalence survey programmes”, medRxiv.