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Pattern recognition display methods for the analysis of computed molecular properties

https://doi.org/10.1007/bf01590995
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What this work says

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

inferredcites →https://doi.org/10.1002/bms.1200030402openalex-snapshot
Applications of computerized pattern recognition: A survey of correlations between pharmacological activities and mass spectra
inferredcites →https://doi.org/10.1007/978-1-4899-3184-9_4openalex-snapshot
Principal component analysis
inferredcites →https://doi.org/10.1007/bf01532089openalex-snapshot
Perspectives in QSAR: Computer chemistry and pattern recognition
inferredcites →https://doi.org/10.1016/0031-3203(76)90023-6openalex-snapshot
An orthogonal feature selection method
inferredcites →https://doi.org/10.1016/0166-6851(88)90029-1openalex-snapshot
Physicochemical characteristics of non-electrolytes and their uptake by Brugia pahangi and Dipetalonema viteae
inferredcites →https://doi.org/10.1016/0263-7855(87)80004-8openalex-snapshot
Computer program suite for the calculation, storage and manipulation of molecular property and activity descriptors
inferredcites →https://doi.org/10.1021/ja00771a016openalex-snapshot
Pattern recognition. Powerful approach to interpreting chemical data
inferredcites →https://doi.org/10.1021/ja00784a007openalex-snapshot
Pattern recognition. II. Linear and nonlinear methods for displaying chemical data
inferredcites →https://doi.org/10.1021/jm00196a017openalex-snapshot
Chance factors in studies of quantitative structure-activity relationships
inferredcites →https://doi.org/10.1021/jm00250a008openalex-snapshot
Discriminant analysis of the relation between physical properties and the inhibition of monoamine oxidase by aminotetralins and aminoindans
inferredcites →https://doi.org/10.1080/00401706.1983.10487903openalex-snapshot
Introduction to Multivariate Analysis
inferredcites →https://doi.org/10.1109/t-c.1969.222678openalex-snapshot
A Nonlinear Mapping for Data Structure Analysis
inferredcites →https://doi.org/10.2307/2258011openalex-snapshot
Multivariate Statistical Analysis for Biologists.
inferredcites →https://doi.org/10.2307/2985346openalex-snapshot
Multivariate Statistical Analysis for Biologists.

What points at this work

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

inferred← citeshttps://doi.org/10.1002/9780470017913.ch4openalex-snapshot
Data Display
inferred← citeshttps://doi.org/10.1002/9780470017913.ch9openalex-snapshot
Artificial Intelligence and Friends
inferred← citeshttps://doi.org/10.1002/9783527615452.ch4openalex-snapshot
Multivariate Data Analysis of Chemical and Biological Data
inferred← citeshttps://doi.org/10.1002/9783527615674.ch5openalex-snapshot
Neural Networks and Expert Systems in Molecular Design
inferred← citeshttps://doi.org/10.1002/cem.1180040504openalex-snapshot
U. K. usage of chemometrics and artificial intelligence in QSAR analysis
inferred← citeshttps://doi.org/10.1002/cem.1180070402openalex-snapshot
Non‐linear mapping for structure‐activity and structure‐property modelling
inferred← citeshttps://doi.org/10.1002/jccs.200800051openalex-snapshot
Partition Coefficient Prediction of a Large Set of Various Drugs and Poisons by a Genetic Algorithm and Artificial Neural Network
inferred← citeshttps://doi.org/10.1002/ps.2780270309openalex-snapshot
Multivariate quantitative structure‐activity relationship (QSAR) methods which may be applied to pesticide research
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The Use of Artificial Neural Networks in QSAR
inferred← citeshttps://doi.org/10.1002/qsar.19900090206openalex-snapshot
Multivariate Techniques for Parameter Selection and Data Analysis Exemplified by a Study of Pyrethroid Neurotoxicity
inferred← citeshttps://doi.org/10.1002/qsar.19960150402openalex-snapshot
Parameter Based Methods for Compound Selection from Chemical Databases
inferred← citeshttps://doi.org/10.1002/qsar.200630021openalex-snapshot
Comparison Between 2D and 3D‐QSAR Approaches to Correlate Inhibitor Activity for a Series of Indole Amide Hydroxamic Acids
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Multivariate QSAR and Computational Chemistry: A Novel Receptor Model of the D1 Agonist Binding Site
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Topics of Chemometrics Today
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3D molecular similarity indices and their application in QSAR studies
inferred← citeshttps://doi.org/10.1007/bf00124364openalex-snapshot
Sample-distance partial least squares: PLS optimized for many variables, with application to CoMFA
inferred← citeshttps://doi.org/10.1007/bf00141575openalex-snapshot
Chiral chromatography and multivariate quantitative structure-property relationships of benzimidazole sulphoxides
inferred← citeshttps://doi.org/10.1007/s00706-011-0554-yopenalex-snapshot
Prediction of the surface tension of surfactant mixtures for detergent formulation using Design Expert software
inferred← citeshttps://doi.org/10.1016/0045-6535(91)90285-lopenalex-snapshot
Graphical display of the fugacity model level I
inferred← citeshttps://doi.org/10.1016/0076-6879(91)03032-copenalex-snapshot
[30] Pattern recognition methods in rational drug design
inferred← citeshttps://doi.org/10.1016/0263-7855(91)85008-mopenalex-snapshot
Novel method for the display of multivariate data using neural networks
inferred← citeshttps://doi.org/10.1016/0300-483x(92)90190-popenalex-snapshot
Multivariate quantitative structure-toxicity relationships in a series of dopamine mimetics
inferred← citeshttps://doi.org/10.1016/b978-012213815-7/50007-8openalex-snapshot
Adaptive Resonance Theory Based Neural Networks Explored for Pattern Recognition Analysis of QSAR data
inferred← citeshttps://doi.org/10.1016/b978-012213815-7/50008-xopenalex-snapshot
Multivariate Data Display Using Neural Networks
inferred← citeshttps://doi.org/10.1016/b978-012213815-7/50011-xopenalex-snapshot
A New Nonlinear Neural Mapping Technique for Visual Exploration of QSAR Data
inferred← citeshttps://doi.org/10.1016/j.bmcl.2007.11.134openalex-snapshot
3D-QSAR models on clinically relevant K103N mutant HIV-1 reverse transcriptase obtained from two strategic considerations
inferred← citeshttps://doi.org/10.1016/j.ejmech.2010.02.027openalex-snapshot
A computational study of the binding of 3-(arylidene) anabaseines to two major brain nicotinic acetylcholine receptors and to the acetylcholine binding protein
inferred← citeshttps://doi.org/10.1016/s0003-2670(03)00468-9openalex-snapshot
Prediction of bioconcentration factor using genetic algorithm and artificial neural network
inferred← citeshttps://doi.org/10.1016/s0026-895x(25)11071-7openalex-snapshot
Application of pattern recognition methods to the analysis and classification of toxicological data derived from proton nuclear magnetic resonance spectroscopy of urine.
inferred← citeshttps://doi.org/10.1016/s0079-6107(98)00026-1openalex-snapshot
Artificial neural networks for computer-based molecular design
inferred← citeshttps://doi.org/10.1016/s1093-3263(00)00065-6openalex-snapshot
Visualizing substructural fingerprints
inferred← citeshttps://doi.org/10.1021/jm9507035openalex-snapshot
Evolutionary Optimization in Quantitative Structure−Activity Relationship: An Application of Genetic Neural Networks
inferred← citeshttps://doi.org/10.1023/a:1007538517470openalex-snapshot
2D and 3D QSAR Analysis of Some Valproic Acid Metabolites and Analogues as Anticonvulsant Agents
inferred← citeshttps://doi.org/10.1023/a:1008074223811openalex-snapshot
Data modelling with neural networks: Advantages and limitations
inferred← citeshttps://doi.org/10.1039/ai9943100107openalex-snapshot
Quantitative structure–activity relationships: correlation and similarity methods
inferred← citeshttps://doi.org/10.1111/j.1528-1157.1994.tb02454.xopenalex-snapshot
Quantum Pharmacologic Studies Applicable to the Design of Anticonvulsants: Theoretical Conformational Analysis and Structure‐Activity Studies of Barbiturates
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Use of genetic algorithms and artificial neural networks to predict the resolution of amino acids in thin-layer chromatography
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Design of Anticancer Agents Utilizing Streptozocin for In Silico Optimiza-tion of Properties and Pattern Recognition Identification of Group Features
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