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Three Useful Dimensions for Domain Applicability in QSAR Models Using Random Forest.. J. Chem. Inf. Model., 52 (3): 814-823 (2012)Molecular Transformations as a Way of Finding and Exploiting Consistent Local QSAR., , and . J. Chem. Inf. Model., 46 (1): 180-192 (2006)Designing novel nicotinic agonists by searching a database of molecular shapes., and . J. Comput. Aided Mol. Des., 1 (3): 243-256 (1987)A Method for Visualizing Recurrent Topological Substructures in Sets of Active Molecules., and . Journal of Chemical Information and Computer Sciences, 38 (5): 915-924 (1998)Correction to Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships., , , , and . J. Chem. Inf. Model., 60 (3): 1910 (2020)Is Multitask Deep Learning Practical for Pharma?, , , , , , and . J. Chem. Inf. Model., 57 (8): 2068-2076 (August 2017)Experimental Error, Kurtosis, Activity Cliffs, and Methodology: What Limits the Predictivity of Quantitative Structure-Activity Relationship Models?, , , , , , , , , and . J. Chem. Inf. Model., 60 (4): 1969-1982 (2020)Light Gradient Boosting Machine as a Regression Method for Quantitative Structure-Activity Relationships., , and . CoRR, (2021)The Most Common Chemical Replacements in Drug-Like Compounds.. Journal of Chemical Information and Computer Sciences, 42 (1): 103-108 (2002)The Centroid Approximation for Mixtures: Calculating Similarity and Deriving Structure-Activity Relationships.. Journal of Chemical Information and Computer Sciences, 40 (6): 1456-1469 (2000)