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Neural Network Modeling for Estimation of Partition Coefficient Based on Atom-Type Electrotopological State Indices

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Outgoing claims: the papers this work cites, builds on, or argues with.

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Calculation of partition coefficients by the charge density method

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Assessment of methods used for predicting lipophilicity: Application to nucleosides and nucleoside bases

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Substituent Constants for Correlation Analysis in Chemistry and Biology.

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Atom/Fragment Contribution Method for Estimating Octanol–Water Partition Coefficients

inferredcites →https://doi.org/10.1007/s008940050027openalex-snapshot

Prediction of the n-Octanol/Water Partition Coefficient, logP, Using a Combination of Semiempirical MO-Calculations and a Neural Network

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Autocorrelation modeling of lipophilicity with a back-propagation neural network

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Efficient Partition of Learning Data Sets for Neural Network Training

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Aqueous Solubility Prediction of Drugs Based on Molecular Topology and Neural Network Modeling

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Identification of Biological Activity Profiles Using Substructural Analysis and Genetic Algorithms

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Modeling Antileukemic Activity of Carboquinones with Electrotopological State and Chi Indices

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The Characterization of Chemical Structures Using Molecular Properties. A Survey

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Molecular Size Based Approach To Estimate Partition Properties for Organic Solutes

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Neural Network Modeling for Estimation of the Aqueous Solubility of Structurally Related Drugs

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Prediction of partition coefficient based on atom‐type electrotopological state indices

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Octanol-Water Partition: Searching for Predictive Models

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