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Alpha Shapes Applied to Molecular Shape Characterization Exhibit Novel Properties Compared to Established Shape Descriptors., , , и . Journal of Chemical Information and Modeling, 49 (10): 2231-2241 (2009)Support vector inductive logic programming outperforms the naive Bayes classifier and inductive logic programming for the classification of bioactive chemical compounds., , , , , , и . J. Comput. Aided Mol. Des., 21 (5): 269-280 (2007)Conformal Regression for Quantitative Structure-Activity Relationship Modeling - Quantifying Prediction Uncertainty., , , , , , и . J. Chem. Inf. Model., 58 (5): 1132-1140 (2018)Similarity Searching of Chemical Databases Using Atom Environment Descriptors (MOLPRINT 2D): Evaluation of Performance., , , и . J. Chem. Inf. Model., 44 (5): 1708-1718 (2004)General Melting Point Prediction Based on a Diverse Compound Data Set and Artificial Neural Networks., , и . J. Chem. Inf. Model., 45 (3): 581-590 (2005)Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Prediction Errors for Deep Neural Networks., и . J. Chem. Inf. Model., 59 (3): 1269-1281 (2019)Discovering Highly Potent Molecules from an Initial Set of Inactives Using Iterative Screening., , , и . J. Chem. Inf. Model., 58 (9): 2000-2014 (2018)Substructure Mining of GPCR Ligands Reveals Activity-Class Specific Functional Groups in an Unbiased Manner., , , и . J. Chem. Inf. Model., 49 (2): 348-360 (2009)Reliable Prediction Errors for Deep Neural Networks Using Test-Time Dropout., и . J. Chem. Inf. Model., 59 (7): 3330-3339 (2019)A Discussion of Measures of Enrichment in Virtual Screening: Comparing the Information Content of Descriptors with Increasing Levels of Sophistication., и . J. Chem. Inf. Model., 45 (5): 1369-1375 (2005)