Sally R. Ellingson
Affiliations: | 2010-2014 | University of Kentucky, Lexington, KY |
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| Mukta FT, Rana MM, Meyer A, et al. (2025) The algebraic extended atom-type graph-based model for precise ligand-receptor binding affinity prediction. Journal of Cheminformatics. 17: 10 |
| Acharya A, Agarwal R, Baker M, et al. (2020) Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19. Chemrxiv : the Preprint Server For Chemistry |
| Ellingson SR, Davis B, Allen J. (2020) Machine learning and ligand binding predictions: A review of data, methods, and obstacles. Biochimica Et Biophysica Acta. General Subjects. 129545 |
| Evangelista W, Ellingson SR, Smith JC, et al. (2019) Ensemble Docking in Drug Discovery: How Many Protein Configurations from Molecular Dynamics Simulations Are Needed to Reproduce Known Ligand Binding? The Journal of Physical Chemistry. B |
| Alghamedy F, Bopaiah J, Jones D, et al. (2018) Incorporating Protein Dynamics Through Ensemble Docking in Machine Learning Models to Predict Drug Binding. Amia Joint Summits On Translational Science Proceedings. Amia Joint Summits On Translational Science. 2017: 26-34 |
| Evangelista W, Weir RL, Ellingson SR, et al. (2016) Ensemble-based docking: From hit discovery to metabolism and toxicity predictions. Bioorganic & Medicinal Chemistry |
| Ellingson SR, Miao Y, Baudry J, et al. (2015) Multi-conformer ensemble docking to difficult protein targets. The Journal of Physical Chemistry. B. 119: 1026-34 |
| Ellingson SR, Wang C, Nagarajan R. (2015) Convex-hull voting method on a large data set Bmc Bioinformatics. 16 |
| Ellingson SR, Dakshanamurthy S, Brown M, et al. (2014) Accelerating Virtual High-Throughput Ligand Docking: current technology and case study on a petascale supercomputer. Concurrency and Computation : Practice & Experience. 26: 1268-1277 |
| Ellingson SR, Smith JC, Baudry J. (2014) Polypharmacology and supercomputer-based docking: Opportunities and challenges Molecular Simulation. 40: 848-854 |