Robert P. Sheridan

Publication Activity (10 Years)

Years Active: 1987-2023
Publications (10 Years): 17

Top Topics

Gradient Boosting

Nearest Neighbor

Machine Learning

Top Venues

J. Chem. Inf. Model.

Publications

Yuting Xu, Andy Liaw, Robert P. Sheridan, Vladimir Svetnik
Development and Evaluation of Conformal Prediction Methods for QSAR. CoRR (2023)
Robert P. Sheridan, J. Christopher Culberson, Elizabeth Joshi, Matthew Tudor, Prabha Karnachi
Prediction Accuracy of Production ADMET Models as a Function of Version: Activity Cliffs Rule. J. Chem. Inf. Model. 62 (14) (2022)
Robert P. Sheridan
Stability of Prediction in Production ADMET Models as a Function of Version: Why and When Predictions Change. J. Chem. Inf. Model. 62 (15) (2022)
Robert P. Sheridan, Andy Liaw, Matthew Tudor
Light Gradient Boosting Machine as a Regression Method for Quantitative Structure-Activity Relationships. CoRR (2021)
Robert P. Sheridan, Min Wang, Andy Liaw, Junshi Ma, Eric M. Gifford
Correction to Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 60 (3) (2020)
Robert P. Sheridan, Prabha Karnachi, Matthew Tudor, Yuting Xu, Andy Liaw, Falgun Shah, Alan C. Cheng, Elizabeth Joshi, Meir Glick, Juan Alvarez
Experimental Error, Kurtosis, Activity Cliffs, and Methodology: What Limits the Predictivity of Quantitative Structure-Activity Relationship Models? J. Chem. Inf. Model. 60 (4) (2020)
Anthony Difranzo, Robert P. Sheridan, Andy Liaw, Matthew Tudor
Nearest Neighbor Gaussian Process for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 60 (10) (2020)
Roc Reguant, Yevgeniy Antipin, Robert P. Sheridan, Christian Dallago, Drew Diamantoukos, Augustin Luna, Chris Sander, Nicholas Paul Gauthier
AlignmentViewer: Sequence Analysis of Large Protein Families. F1000Research 9 (2020)
Yuting Xu, Deeptak Verma, Robert P. Sheridan, Andy Liaw, Junshui Ma, Nicholas M. Marshall, John McIntosh, Edward C. Sherer, Vladimir Svetnik, Jennifer M. Johnston
Deep Dive into Machine Learning Models for Protein Engineering. J. Chem. Inf. Model. 60 (6) (2020)
Robert P. Sheridan
Interpretation of QSAR Models by Coloring Atoms According to Changes in Predicted Activity: How Robust Is It? J. Chem. Inf. Model. 59 (4) (2019)
Evan N. Feinberg, Robert P. Sheridan, Elizabeth Joshi, Vijay S. Pande, Alan C. Cheng
Step Change Improvement in ADMET Prediction with PotentialNet Deep Featurization. CoRR (2019)
Dai Feng, Vladimir Svetnik, Andy Liaw, Matthew T. Pratola, Robert P. Sheridan
Building Quantitative Structure-Activity Relationship Models Using Bayesian Additive Regression Trees. J. Chem. Inf. Model. 59 (6) (2019)
Thomas A. Hopf, Anna G. Green, Benjamin Schubert, Sophia Mersmann, Charlotta Schärfe, John Ingraham, Ágnes Tóth-Petróczy, Kelly Brock, Adam J. Riesselman, Perry Palmedo, Chan Kang, Robert P. Sheridan, Eli J. Draizen, Christian Dallago, Chris Sander, Debora S. Marks
The EVcouplings Python framework for coevolutionary sequence analysis. Bioinform. 35 (9) (2019)
Yuting Xu, Junshui Ma, Andy Liaw, Robert P. Sheridan, Vladimir Svetnik
Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 57 (10) (2017)
Bharath Ramsundar, Bowen Liu, Zhenqin Wu, Andreas Verras, Matthew Tudor, Robert P. Sheridan, Vijay S. Pande
Is Multitask Deep Learning Practical for Pharma? J. Chem. Inf. Model. 57 (8) (2017)
Robert P. Sheridan
Debunking the Idea that Ligand Efficiency Indices Are Superior to pIC50 as QSAR Activities. J. Chem. Inf. Model. 56 (11) (2016)
Robert P. Sheridan, Wei Min Wang, Andy Liaw, Junshui Ma, Eric M. Gifford
Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 56 (12) (2016)
Robert P. Sheridan, Daniel R. McMasters, Johannes H. Voigt, Mary Jo Wildey
eCounterscreening: Using QSAR Predictions to Prioritize Testing for Off-Target Activities and Setting the Balance between Benefit and Risk. J. Chem. Inf. Model. 55 (2) (2015)
Junshui Ma, Robert P. Sheridan, Andy Liaw, George E. Dahl, Vladimir Svetnik
Deep Neural Nets as a Method for Quantitative Structure-Activity Relationships. J. Chem. Inf. Model. 55 (2) (2015)
Robert P. Sheridan
The Relative Importance of Domain Applicability Metrics for Estimating Prediction Errors in QSAR Varies with Training Set Diversity. J. Chem. Inf. Model. 55 (6) (2015)
Robert P. Sheridan
Global Quantitative Structure-Activity Relationship Models vs Selected Local Models as Predictors of Off-Target Activities for Project Compounds. J. Chem. Inf. Model. 54 (4) (2014)
Robert P. Sheridan, Nicolas Zorn, Edward C. Sherer, Louis-Charles Campeau, Charlie (Zhenyu) Chang, Jared Cumming, Matthew L. Maddess, Philippe G. Nantermet, Christopher J. Sinz, Paul D. O'Shea
Modeling a Crowdsourced Definition of Molecular Complexity. J. Chem. Inf. Model. 54 (6) (2014)
Robert P. Sheridan
Using Random Forest To Model the Domain Applicability of Another Random Forest Model. J. Chem. Inf. Model. 53 (11) (2013)
Robert P. Sheridan
Time-Split Cross-Validation as a Method for Estimating the Goodness of Prospective Prediction. J. Chem. Inf. Model. 53 (4) (2013)
Bin Chen, Robert P. Sheridan, Viktor Hornak, Johannes H. Voigt
Comparison of Random Forest and Pipeline Pilot Naïve Bayes in Prospective QSAR Predictions. J. Chem. Inf. Model. 52 (3) (2012)
Robert P. Sheridan
Three Useful Dimensions for Domain Applicability in QSAR Models Using Random Forest. J. Chem. Inf. Model. 52 (3) (2012)
Debora S. Marks, Lucy J. Colwell, Robert P. Sheridan, Thomas A. Hopf, Andrea Pagnani, Riccardo Zecchina, Chris Sander
3D Protein Structure Predicted from Sequence CoRR (2011)
Robert P. Sheridan, Vladimir N. Maiorov, M. Katharine Holloway, Wendy D. Cornell, Ying-Duo Gao
Drug-like Density: A Method of Quantifying the "Bindability" of a Protein Target Based on a Very Large Set of Pockets and Drug-like Ligands from the Protein Data Bank. J. Chem. Inf. Model. 50 (11) (2010)
Junshui Ma, Christopher Tong, Andy Liaw, Robert P. Sheridan, John Szumiloski, Vladimir Svetnik
Generating hypotheses about molecular structure-activity relationships (SARs) by solving an optimization problem. Stat. Anal. Data Min. 2 (3) (2009)
Robert P. Sheridan, Kiyean Nam, Vladimir N. Maiorov, Daniel R. McMasters, Wendy D. Cornell
QSAR Models for Predicting the Similarity in Binding Profiles for Pairs of Protein Kinases and the Variation of Models between Experimental Data Sets. J. Chem. Inf. Model. 49 (8) (2009)
Robert P. Sheridan, Georgia B. McGaughey, Wendy D. Cornell
Multiple protein structures and multiple ligands: effects on the apparent goodness of virtual screening results. J. Comput. Aided Mol. Des. 22 (3-4) (2008)
Robert P. Sheridan
Alternative Global Goodness Metrics and Sensitivity Analysis: Heuristics to Check the Robustness of Conclusions from Studies Comparing Virtual Screening Methods. J. Chem. Inf. Model. 48 (2) (2008)
Doron Betel, Robert P. Sheridan, Debora S. Marks, Chris Sander
Computational Analysis of Mouse piRNA Sequence and Biogenesis. PLoS Comput. Biol. 3 (11) (2007)
Georgia B. McGaughey, Robert P. Sheridan, Christopher I. Bayly, J. Christopher Culberson, Constantine Kreatsoulas, Stacey Lindsley, Vladimir N. Maiorov, Jean-François Truchon, Wendy D. Cornell
Comparison of Topological, Shape, and Docking Methods in Virtual Screening. J. Chem. Inf. Model. 47 (4) (2007)
Robert P. Sheridan, Peter Hunt, J. Christopher Culberson
Molecular Transformations as a Way of Finding and Exploiting Consistent Local QSAR. J. Chem. Inf. Model. 46 (1) (2006)
Ralph T. Mosley, J. Christopher Culberson, Bryan Kraker, Bradley P. Feuston, Robert P. Sheridan, John F. Conway, Joseph K. Forbes, Subhas J. Chakravorty, Simon K. Kearsley
Reagent Selector: Using Synthon Analysis to Visualize Reagent Properties and Assist in Combinatorial Library Design. J. Chem. Inf. Model. 45 (5) (2005)
Vladimir Svetnik, Ting Wang, Christopher Tong, Andy Liaw, Robert P. Sheridan, Qinghua Song
Boosting: An Ensemble Learning Tool for Compound Classification and QSAR Modeling. J. Chem. Inf. Model. 45 (3) (2005)
Vladimir N. Maiorov, Robert P. Sheridan
Enhanced Virtual Screening by Combined Use of Two Docking Methods: Getting the Most on a Limited Budget. J. Chem. Inf. Model. 45 (4) (2005)
Robert P. Sheridan, Joseph Shpungin
Calculating Similarities between Biological Activities in the MDL Drug Data Report Database. J. Chem. Inf. Model. 44 (2) (2004)
Robert P. Sheridan, Bradley P. Feuston, Vladimir N. Maiorov, Simon K. Kearsley
Similarity to Molecules in the Training Set Is a Good Discriminator for Prediction Accuracy in QSAR. J. Chem. Inf. Model. 44 (6) (2004)
Robert P. Sheridan
Finding Multiactivity Substructures by Mining Databases of Drug-Like Compounds. J. Chem. Inf. Comput. Sci. 43 (3) (2003)
Vladimir Svetnik, Andy Liaw, Christopher Tong, J. Christopher Culberson, Robert P. Sheridan, Bradley P. Feuston
Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling. J. Chem. Inf. Comput. Sci. 43 (6) (2003)
Robert P. Sheridan
The Most Common Chemical Replacements in Drug-Like Compounds. J. Chem. Inf. Comput. Sci. 42 (1) (2002)
Robert P. Sheridan, Suresh B. Singh, Eugene M. Fluder, Simon K. Kearsley
Protocols for Bridging the Peptide to Nonpeptide Gap in Topological Similarity Searches. J. Chem. Inf. Comput. Sci. 41 (5) (2001)
Robert P. Sheridan
The Centroid Approximation for Mixtures: Calculating Similarity and Deriving Structure-Activity Relationships. J. Chem. Inf. Comput. Sci. 40 (6) (2000)
Robert P. Sheridan, Michael D. Miller
A Method for Visualizing Recurrent Topological Substructures in Sets of Active Molecules. J. Chem. Inf. Comput. Sci. 38 (5) (1998)
Robert P. Sheridan, Michael D. Miller, Dennis J. Underwood, Simon K. Kearsley
Chemical Similarity Using Geometric Atom Pair Descriptors. J. Chem. Inf. Comput. Sci. 36 (1) (1996)
Simon K. Kearsley, Susan Sallamack, Eugene M. Fluder, Joseph D. Andose, Ralph T. Mosley, Robert P. Sheridan
Chemical Similarity Using Physiochemical Property Descriptors. J. Chem. Inf. Comput. Sci. 36 (1) (1996)
Robert P. Sheridan, Simon K. Kearsley
Using a Genetic Algorithm To Suggest Combinatorial Libraries. J. Chem. Inf. Comput. Sci. 35 (2) (1995)
Simon K. Kearsley, Dennis J. Underwood, Robert P. Sheridan, Michael D. Miller
Flexibases: A way to enhance the use of molecular docking methods. J. Comput. Aided Mol. Des. 8 (5) (1994)
Robert P. Sheridan, Robert B. Nachbar, Bruce L. Bush
Extending the trend vector: The trend matrix and sample-based partial least squares. J. Comput. Aided Mol. Des. 8 (3) (1994)
Michael D. Miller, Simon K. Kearsley, Dennis J. Underwood, Robert P. Sheridan
FLOG: A system to select 'quasi-flexible' ligands complementary to a receptor of known three-dimensional structure. J. Comput. Aided Mol. Des. 8 (2) (1994)
Bruce L. Bush, Robert P. Sheridan
PATTY: A programmable atom type and language for automatic classification of atoms in molecular databases. J. Chem. Inf. Comput. Sci. 33 (5) (1993)
Robert P. Sheridan, Ramaswamy Nilakantan, Andrew Rusinko III, Norman Bauman, Kevin S. Haraki, R. Venkataraghavan
3DSEARCH: a system for three-dimensional substructure searching. J. Chem. Inf. Comput. Sci. 29 (4) (1989)
Andrew Rusinko III, Robert P. Sheridan, Ramaswamy Nilakantan, Kevin S. Haraki, Norman Bauman, R. Venkataraghavan
Using CONCORD to construct a large database of three-dimensional coordinates from connection tables. J. Chem. Inf. Comput. Sci. 29 (4) (1989)
Robert P. Sheridan, R. Venkataraghavan
Designing novel nicotinic agonists by searching a database of molecular shapes. J. Comput. Aided Mol. Des. 1 (3) (1987)