Jackson Burns

MacDermott-Opeskin H, Scheen J, Wognum C, Horton JT, West D, Payne AM, et al. A Computational Community Blind Challenge on Pan-Coronavirus Drug Discovery Data. ChemRxiv. 2025; doi:10.26434/chemrxiv-2025-zd9mr-v2 preprint

Burns, J., Zalte, A., & Green, W. (2025, June 18). Descriptor-based foundation models for Molecular Property Prediction. arXiv.org. https://arxiv.org/abs/2506.15792

Burns, J.W., Green, W.H. Generalizable, fast, and accurate DeepQSPR with fastprop. J Cheminform 17, 73 (2025). https://doi.org/10.1186/s13321-025-01013-4

Burns, J.W., Attia, L., Doyle, P.S. et al. Data-driven organic solubility prediction at the limit of aleatoric uncertainty. Nat Commun 16, 7497 (2025). https://doi.org/10.1038/s41467-025-62717-7

Jackson W. Burns and David M. Rogers, QuantumScents: Quantum-Mechanical Properties for 3.5k Olfactory Molecules, Journal of Chemical Information and Modeling 2023 63 (23), 7330-7337. DOI: 10.1021/acs.jcim.3c01338

Burns et al., (2023). Machine Learning Validation via Rational Dataset Sampling with astartes. Journal of Open Source Software, 8(91), 5996, DOI: 10.21105/joss.05996

Jackson Burns, Himaghna Bhattacharjee, Dionisios G. Vlachos, AIMSim: An accessible cheminformatics platform for similarity operations on chemicals datasets, Computer Physics Communications, Volume 283, 2023, 108579, ISSN 0010-4655, DOI: 10.1016/j.cpc.2022.108579.