Sheridan, Robert P.
Merck & Co., Inc., Rahway, NJ, USA (United States)
8 papers on CoChatORCID 0000-0002-6549-1635
Most cited papers
- Verified
Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships
Ma, J., Sheridan, R. P., Liaw, A., Dahl, G. E., & Svetnik, V. (2015) · Journal of Chemical Information and Modeling
Computational Drug Discovery MethodsMachine Learning in Materials Science
Cited by 1,159
- Verified
QSAR without borders
Muratov, E. N., Bajorath, J., Sheridan, R. P., Tetko, I. V., Filimonov, D., Poroikov, V., Oprea, T. I., Baskin, I. I., Varnek, A., Roitberg, A., et al. (2020) · Chemical Society Reviews
Computational Drug Discovery MethodsMachine Learning in Materials Science
Cited by 913
- Verified
Extreme Gradient Boosting as a Method for Quantitative Structure–Activity Relationships
Sheridan, R. P., Wang, W. M., Liaw, A., Ma, J., & Gifford, E. M. (2016) · Journal of Chemical Information and Modeling
Computational Drug Discovery MethodsMachine Learning in Materials Science
Cited by 544
- Verified
Why do we need so many chemical similarity search methods?
Sheridan, R. (2002) · Drug Discovery Today
Computational Drug Discovery MethodsSynthesis and Characterization of Heterocyclic Compounds
Cited by 412
- Verified
Time-Split Cross-Validation as a Method for Estimating the Goodness of Prospective Prediction.
Sheridan, R. P. (2013) · Journal of Chemical Information and Modeling
Computational Drug Discovery MethodsMachine Learning in Materials Science
Cited by 376
- Verified
Is Multitask Deep Learning Practical for Pharma?
Ramsundar, B., Liu, B., Wu, Z., Verras, A., Tudor, M., Sheridan, R. P., & Pande, V. (2017) · Journal of Chemical Information and Modeling
Computational Drug Discovery MethodsMachine Learning in Materials Science
Cited by 263
- Verified
Demystifying Multitask Deep Neural Networks for Quantitative Structure–Activity Relationships
Xu, Y., Ma, J., Liaw, A., Sheridan, R. P., & Svetnik, V. (2017) · Journal of Chemical Information and Modeling
Computational Drug Discovery MethodsMachine Learning in Materials Science
Cited by 238
- Verified
Interpretation of QSAR Models by Coloring Atoms According to Changes in Predicted Activity: How Robust Is It?
Sheridan, R. P. (2019) · Journal of Chemical Information and Modeling
Computational Drug Discovery MethodsAdvanced Chemical Physics Studies
Cited by 84
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