Dr Daniel Allen Nissley

Florence Nightingale Bicentenary Research Fellow and Tutor in Bioinformatics

About Me

I am a chemist by training, completing my BSc at Lehigh University in 2013 and my Ph.D. at Penn State University in Ed O’Brien’s lab in 2019. I came to work with Charlotte Deane in the Oxford Protein Informatics Group (OPIG) as a postdoc in 2019 and began my current role as a Florence Nightingale Fellow in 2020. In 2021 I started working with Frank von Delft in the Oxford Center for Medicines Discovery, and in 2022 joined a project funded by Boehringer-Ingelheim.

Research Interests

I am broadly interested in using molecular modeling and simulation techniques to understand structure-function relationships in biological systems. While my Ph.D. research focused on co-translational protein folding and how the speed of protein synthesis can influence folding, since joining OPIG I have branched out into studies of antibodies, bispecifics, immunology, and protein engineering.

Publications

Eales, O., Haw, D., Wang, H., Atchison, C., Ashby, D., Cooke, G., Barclay, W., Ward, H., Darzi, A., Donnelly, C., Chadeau-Hyam, M., Elliott, P. and Riley, S. (2023) “Dynamics of SARS-CoV-2 infection hospitalisation and infection fatality ratios over 23 months in England.”, PLoS biology, 21(5), p. e3002118.

Zhang, Y., Cucuringu, M., Shestopaloff, A. and Zohren, S. (2023) “Robust Detection of Lead-Lag Relationships in Lagged Multi-Factor Models.”

Scantlebury, J., Vost, L., Carbery, A., Hadfield, T., Turnbull, O., Brown, N., Chenthamarakshan, V., Das, P., Grosjean, H., von Delft, F. and Deane, C. (2023) “A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening”, Journal of Chemical Information and Modeling [Preprint].

Homberg, S., Janosch, M., Morris, G. and Koch, O. (2023) “Interpreting Graph Neural Networks with Myerson Values for Cheminformatics Approaches”, American Chemical Society (ACS).

Goldschmidt, C. and Stephenson, R. (2023) “The scaling limit of a critical random directed graph”, Annals of Applied Probability, 33(3), pp. 2024–2065.

Wills, S., Sanchez-Garcia, R., Dudgeon, T., Roughley, S., Merritt, A., Hubbard, R., Davidson, J., von Delft, F. and Deane, C. (2023) “Fragment Merging Using a Graph Database Samples Different Catalogue Space than Similarity Search.”, Journal of chemical information and modeling [Preprint].

Doucet, A., Moulines, E. and Thin, A. (2023) “Differentiable samplers for deep latent variable models.”, Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 381(2247), p. 20220147.

Robert, C. and Rousseau, J. (2023) “A special issue on Bayesian inference: challenges, perspectives and prospects.”, Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 381(2247), p. 20220155.

Zhang, B., Biddanda, A., Gunnarsson, A., Cooper, F. and Palamara, P. (2023) “Biobank-scale inference of ancestral recombination graphs enables genealogical analysis of complex traits”, Nature Genetics, 55, pp. 768–776.

Holmes, C. and Walker, S. (2023) “Statistical inference with exchangeability and martingales.”, Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 381(2247), p. 20220143.

Contact Details

Email: daniel.nissley@stats.ox.ac.uk

Office: 2.11

Pronouns: He/Him

Research Groups

Oxford Protein Informatics Group