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Differential Shannon Entropy Analysis Identifies Molecular Property Descriptors that Predict Aqueous Solubility of Synthetic Compounds with High Accuracy in Binary QSAR Calculations
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Statistical Investigation into the Structural Complementarity of Natural Products and Synthetic Compounds
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A widely applicable set of descriptors
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Selected Concepts and Investigations in Compound Classification, Molecular Descriptor Analysis, and Virtual Screening
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Distinguishing between Natural Products and Synthetic Molecules by Descriptor Shannon Entropy Analysis and Binary QSAR Calculations
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Prediction of Aqueous Solubility of Heteroatom-Containing Organic Compounds from Molecular Structure
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Differential Shannon Entropy as a Sensitive Measure of Differences in Database Variability of Molecular Descriptors
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Prediction of Aqueous Solubility for a Diverse Set of Heteroatom-Containing Organic Compounds Using a Quantitative Structure−Property Relationship
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Aqueous Solubility Prediction of Drugs Based on Molecular Topology and Neural Network Modeling
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The Characterization of Chemical Structures Using Molecular Properties. A Survey
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An Introduction to Probability Theory and its Applications.
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Degree‐Based Hybrid Topological Indices and Entropies of Wavy Zigzag Nanoribbons
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Additional file 1 of Harnessing Shannon entropy-based descriptors in machine learning models to enhance the prediction accuracy of molecular properties
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