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Analysis of the Internal Representations Developed by Neural Networks for Structures Applied to Quantitative Structure−Activity Relationship Studies of Benzodiazepines

https://doi.org/10.1021/ci9903399
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inferredcites →https://doi.org/10.1002/9780470125793.ch9openalex-snapshot
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inferredcites →https://doi.org/10.1007/3-540-61577-6openalex-snapshot
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inferredcites →https://doi.org/10.1021/ci00027a017openalex-snapshot
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inferredcites →https://doi.org/10.1021/cr00024a001openalex-snapshot
Feed-forward neural networks in chemistry: mathematical systems for classification and pattern recognition
inferredcites →https://doi.org/10.1021/cr00030a002openalex-snapshot
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inferredcites →https://doi.org/10.1021/ja01062a035openalex-snapshot
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inferredcites →https://doi.org/10.1080/00401706.1988.10488412openalex-snapshot
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inferredcites →https://doi.org/10.1109/ijcnn.1998.682247openalex-snapshot
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Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/chin.200120230openalex-snapshot
ChemInform Abstract: Analysis of the Internal Representations Developed by Neural Networks for Structures Applied to Quantitative Structure—Activity Relationship Studies of Benzodiazepines.
inferred← citeshttps://doi.org/10.1002/masy.200650203openalex-snapshot
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inferred← citeshttps://doi.org/10.1002/minf.201000079openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/3-540-44668-0_2openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-0-387-30440-3_134openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-0-387-88777-7_8openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-1-4471-0715-6_4openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-1-60327-101-1_8openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-030-43883-8_5openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-540-36213-5_10openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-540-39853-0_1openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-540-39853-0_10openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-540-73954-8_4openalex-snapshot
Adaptive Contextual Processing of Structured Data by Recursive Neural Networks: A Survey of Computational Properties
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inferred← citeshttps://doi.org/10.1007/978-3-540-74958-5_32openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10489-011-0300-5openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10910-005-9035-zopenalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10910-009-9547-zopenalex-snapshot
Recursive neural networks prediction of glass transition temperature from monomer structure: an application to acrylic and methacrylic polymers
inferred← citeshttps://doi.org/10.1007/s10994-010-5196-5openalex-snapshot
Neural networks for relational learning: an experimental comparison
inferred← citeshttps://doi.org/10.1007/s11063-009-9109-1openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s11224-022-02029-4openalex-snapshot
Investigation of [3H]diazepam derivatives as allosteric modulators of GABAA receptor α1β2γ2 subtypes: combination of molecular docking/dynamic simulations, pharmacokinetics/drug-likeness prediction, and QSAR analysis
inferred← citeshttps://doi.org/10.1007/s12293-024-00423-5openalex-snapshot
ResGAT: Residual Graph Attention Networks for molecular property prediction
inferred← citeshttps://doi.org/10.1007/springerreference_60306openalex-snapshot
Drug Design with Artificial Neural Networks
inferred← citeshttps://doi.org/10.1016/b978-0-323-85713-0.00030-xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1016/b978-0-443-18638-7.00009-8openalex-snapshot
The impact of artificial intelligence methods on drug design
inferred← citeshttps://doi.org/10.1016/b978-044452855-1/50012-xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.chemolab.2014.06.001openalex-snapshot
A new neural network (tiling-contextual neural network for structures, TC-NNfS) enabling the treatment of relatively small datasets of therapeutic interest: An application to a small dataset of ACE inhibitors
inferred← citeshttps://doi.org/10.1016/j.ins.2018.12.052openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jmgm.2008.12.001openalex-snapshot
Evaluation of hierarchical structured representations for QSPR studies of small molecules and polymers by recursive neural networks
inferred← citeshttps://doi.org/10.1016/j.neucom.2004.11.013openalex-snapshot
A preliminary empirical comparison of recursive neural networks and tree kernel methods on regression tasks for tree structured domains
inferred← citeshttps://doi.org/10.1016/j.neucom.2008.12.021openalex-snapshot
Graph self-organizing maps for cyclic and unbounded graphs
inferred← citeshttps://doi.org/10.1016/j.neucom.2010.05.013openalex-snapshot
Information-theoretic enhancement learning and its application to visualization of self-organizing maps
inferred← citeshttps://doi.org/10.1016/j.neunet.2005.07.007openalex-snapshot
On the relationship between deterministic and probabilistic directed Graphical models: From Bayesian networks to recursive neural networks
inferred← citeshttps://doi.org/10.1016/j.neunet.2005.07.009openalex-snapshot
Graph kernels for chemical informatics
inferred← citeshttps://doi.org/10.1016/j.neunet.2010.12.009openalex-snapshot
Selective information enhancement learning for creating interpretable representations in competitive learning
inferred← citeshttps://doi.org/10.1016/j.neunet.2013.07.007openalex-snapshot
Solving graph data issues using a layered architecture approach with applications to web spam detection
inferred← citeshttps://doi.org/10.1016/j.polymer.2007.09.043openalex-snapshot
Prediction of the glass transition temperature of (meth)acrylic polymers containing phenyl groups by recursive neural network
inferred← citeshttps://doi.org/10.1016/s1076-5670(05)40001-4openalex-snapshot
Recursive Neural Networks and Their Applications to Image Processing
inferred← citeshttps://doi.org/10.1021/acs.jcim.2c01099openalex-snapshot
HiGNN: A Hierarchical Informative Graph Neural Network for Molecular Property Prediction Equipped with Feature-Wise Attention
inferred← citeshttps://doi.org/10.1021/acspolymersau.1c00035openalex-snapshot
Data-Driven Methods for Accelerating Polymer Design
inferred← citeshttps://doi.org/10.1021/ci030340eopenalex-snapshot
Artificial Neural Networks and Linear Discriminant Analysis: A Valuable Combination in the Selection of New Antibacterial Compounds
inferred← citeshttps://doi.org/10.1021/ci060104eopenalex-snapshot
Predicting Physical−Chemical Properties of Compounds from Molecular Structures by Recursive Neural Networks
inferred← citeshttps://doi.org/10.1021/ci200409xopenalex-snapshot
Machine Learning Methods for Property Prediction in Chemoinformatics:Quo Vadis?
inferred← citeshttps://doi.org/10.1021/ci400187yopenalex-snapshot
Deep Architectures and Deep Learning in Chemoinformatics: The Prediction of Aqueous Solubility for Drug-Like Molecules
inferred← citeshttps://doi.org/10.1021/ci600397popenalex-snapshot
One- to Four-Dimensional Kernels for Virtual Screening and the Prediction of Physical, Chemical, and Biological Properties
inferred← citeshttps://doi.org/10.1021/je100535popenalex-snapshot
Quantitative Structure−Property Relationship (QSPR) Prediction of Solvation Gibbs Energy of Bifunctional Compounds by Recursive Neural Networks
inferred← citeshttps://doi.org/10.1039/b708123eopenalex-snapshot
Ionic liquids: prediction of their melting points by a recursive neural network model
inferred← citeshttps://doi.org/10.1080/03081071003601421openalex-snapshot
Information enhancement for interpreting competitive learning
inferred← citeshttps://doi.org/10.1080/09540091.2014.956288openalex-snapshot
Improving visualisation and prediction performance of supervised self-organising map by modified contradiction resolution
inferred← citeshttps://doi.org/10.1080/17460441.2016.1201262openalex-snapshot
A renaissance of neural networks in drug discovery
inferred← citeshttps://doi.org/10.1081/jlc-100108535openalex-snapshot
PCA, FOLLOWED BY TWO-DIMENSIONAL NONLINEAR MAPPING AND CLUSTER ANALYSIS, VERSUS MULTILINEAR REGRESSION IN QSRR
inferred← citeshttps://doi.org/10.1093/bioinformatics/bti1055openalex-snapshot
Kernels for small molecules and the prediction of mutagenicity, toxicity and anti-cancer activity
inferred← citeshttps://doi.org/10.1093/bioinformatics/btm298openalex-snapshot
Classification of small molecules by two- and three-dimensional decomposition kernels
inferred← citeshttps://doi.org/10.1109/72.963781openalex-snapshot
Processing directed acyclic graphs with recursive neural networks
inferred← citeshttps://doi.org/10.1109/ijcnn.2001.938805openalex-snapshot
Design of new biologically active molecules by recursive neural networks
inferred← citeshttps://doi.org/10.1109/ijcnn.2002.1005461openalex-snapshot
Recursive processing of cyclic graphs
inferred← citeshttps://doi.org/10.1109/ijcnn.2009.5178678openalex-snapshot
Selective enhancement learning in competitive learning
inferred← citeshttps://doi.org/10.1109/ijcnn.2018.8489464openalex-snapshot
Deep Tree Echo State Networks
inferred← citeshttps://doi.org/10.1109/ijcnn48605.2020.9206723openalex-snapshot
Ring Reservoir Neural Networks for Graphs
inferred← citeshttps://doi.org/10.1109/tnn.2003.810735openalex-snapshot
A self-organizing map for adaptive processing of structured data
inferred← citeshttps://doi.org/10.1109/tnn.2005.860873openalex-snapshot
Recursive Processing of Cyclic Graphs
inferred← citeshttps://doi.org/10.1109/tnn.2008.2005605openalex-snapshot
The Graph Neural Network Model
inferred← citeshttps://doi.org/10.1145/3503043openalex-snapshot
A Practical Tutorial on Graph Neural Networks
inferred← citeshttps://doi.org/10.1162/153244304773936054openalex-snapshot
10.1162/153244304773936054
inferred← citeshttps://doi.org/10.1201/9780849350351.ch8openalex-snapshot
Neural Networks and Kernel Machines for Vector and Structured Data
inferred← citeshttps://doi.org/10.1385/mb:27:2:139openalex-snapshot
Neural Networks as Robust Tools in Drug Lead Discovery and Development
inferred← citeshttps://doi.org/10.14569/ijarai.2016.050804openalex-snapshot
Information-Theoretic Active SOM for Improving Generalization Performance
inferred← citeshttps://doi.org/10.2174/138161207780765954openalex-snapshot
Artificial Intelligence Approaches for Rational Drug Design and Discovery
inferred← citeshttps://doi.org/10.2174/138161207780765981openalex-snapshot
An Introduction to Recursive Neural Networks and Kernel Methods for Cheminformatics
inferred← citeshttps://doi.org/10.26686/wgtn.25044362openalex-snapshot
De novo Molecular Design using Deep Learning
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