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Neural networks as data mining tools in drug design

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What this work says

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

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Discriminating Toxicant Classes by Mode of Action: 2. Physico-Chemical Descriptors
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Neuronale Netze in der Chemie
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Calculation of the Charge Distribution in Conjugated Systems by a Quantification of the Resonance Concept
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Neural Networks in Chemistry
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Self-Organization and Associative Memory
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Self-organized formation of topologically correct feature maps
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Applications of advances in nonlinear sensitivity analysis
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Iterative partial equalization of orbital electronegativity—a rapid access to atomic charges
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Practical applications of quantitative structure-activity relationships (QSAR) in environmental chemistry and toxicology
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Automatic generation of 3D-atomic coordinates for organic molecules
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Deriving the 3D structure of organic molecules from their infrared spectra
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Comparison of Automatic Three-Dimensional Model Builders Using 639 X-ray Structures
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The Coding of the Three-Dimensional Structure of Molecules by Molecular Transforms and Its Application to Structure-Spectra Correlations and Studies of Biological Activity
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Locating Biologically Active Compounds in Medium-Sized Heterogeneous Datasets by Topological Autocorrelation Vectors: Dopamine and Benzodiazepine Agonists
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From atoms and bonds to three-dimensional atomic coordinates: automatic model builders
inferredcites →https://doi.org/10.1021/ja00134a023openalex-snapshot
Autocorrelation of Molecular Surface Properties for Modeling Corticosteroid Binding Globulin and Cytosolic Ah Receptor Activity by Neural Networks
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Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins
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Counterpropagation networks
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Parallel Distributed Processing

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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