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Machine Learning Methods for Property Prediction in Chemoinformatics: Quo Vadis?, и . Journal of Chemical Information and Modeling, 52 (6): 1413-1437 (2012)An Application of the Miertus-Scrocco-Tomasi Solvation Model in Molecular Mechanics and Dynamics Simulations., , , и . J. Comput. Chem., 16 (1): 1-19 (1995)Structure-reactivity modeling using mixture-based representation of chemical reactions., , , , , и . J. Comput. Aided Mol. Des., 31 (9): 829-839 (2017)Mappability of drug-like space: towards a polypharmacologically competent map of drug-relevant compounds., , , , и . J. Comput. Aided Mol. Des., 29 (12): 1087-1108 (2015)De Novo Molecular Design by Combining Deep Autoencoder Recurrent Neural Networks with Generative Topographic Mapping., , , , , и . J. Chem. Inf. Model., 59 (3): 1182-1196 (2019)Trustworthiness, the Key to Grid-Based Map-Driven Predictive Model Enhancement and Applicability Domain Control., , и . J. Chem. Inf. Model., 60 (12): 6020-6032 (2020)Chemography: Searching for Hidden Treasures., , , , , и . J. Chem. Inf. Model., 61 (1): 179-188 (2021)CGRtools: Python Library for Molecule, Reaction, and Condensed Graph of Reaction Processing., , , , , , и . J. Chem. Inf. Model., 59 (6): 2516-2521 (2019)Predicting the Predictability: A Unified Approach to the Applicability Domain Problem of QSAR Models., , и . Journal of Chemical Information and Modeling, 49 (7): 1762-1776 (2009)QSPR ensemble modelling of the 1: 1 and 1: 2 complexation of Co2+, Ni2+, and Cu2+ with organic ligands: relationships between stability constants., , и . J. Comput. Aided Mol. Des., 28 (5): 549-564 (2014)