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Polarizability Fields for Use in Three-Dimensional Quantitative Structure−Activity Relationship (3D-QSAR)
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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/qsar.19880070105openalex-snapshot
Crossvalidation, Bootstrapping, and Partial Least Squares Compared with Multiple Regression in Conventional QSAR Studies
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HINT: A new method of empirical hydrophobic field calculation for CoMFA
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The polarizability of planar aromatic systems. An application to polychlorinated biphenyls (PCB's), dioxins and polyaromatic hydrocarbons
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Quantum chemistry program exchange
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Comparative molecular field analysis of polyhalogenated dibenzo-p-dioxins, dibenzofurans, and biphenyls
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Analogs of atriopeptin(103-125)amide having high binding selectivity
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Three-Dimensional Quantitative Structure-Activity Relationships of Dioxins and Dioxin-like Compounds: Model Validation and Ah Receptor Characterization
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/chin.200148232openalex-snapshot
ChemInform Abstract: Polarizability Fields for Use in Three‐Dimensional Quantitative Structure—Activity Relationship (3D‐QSAR).
inferred← citeshttps://doi.org/10.1002/etc.2191openalex-snapshot
Docking-based three-dimensional quantitative structure–activity relationship (3D-QSAR) predicts binding affinities to aryl hydrocarbon receptor for polychlorinated dibenzodioxins, dibenzofurans, and biphenyls
inferred← citeshttps://doi.org/10.1002/jps.20449openalex-snapshot
A topological substructural approach for the prediction of P-glycoprotein substrates
inferred← citeshttps://doi.org/10.1002/qsar.200330847openalex-snapshot
Validation of Poisson‐Boltzmann Electrostatic Potential Fields in 3D QSAR: A CoMFA Study on Multiple Datasets
inferred← citeshttps://doi.org/10.1002/qsar.200610003openalex-snapshot
SOMFA on Large Diverse Xenoestrogen Dataset: The Effect of Superposition Algorithms and External Regression Tools
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Vasodilator Effect Through the Signaling Pathway NO-cGMP of Specialized Metabolites into Malvaviscus arboreus: Ex Vivo, QSAR, and Molecular Docking
inferred← citeshttps://doi.org/10.1016/b0-08-045044-x/00142-5openalex-snapshot
Molecular Fields to Assess Recognition Forces and Property Spaces
inferred← citeshttps://doi.org/10.1016/b978-0-12-409547-2.12659-9openalex-snapshot
Molecular Fields to Assess Recognition Forces and Property Spaces☆
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Prediction of binding affinities of PCDDs, PCDFs and PCBs using docking-based Comparative Molecular Similarity Indices Analysis
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A molecular interaction field describing nonconventional intermolecular interactions and its application to protein–ligand interaction prediction
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Molecular Interaction Fields Describing Halogen Bond Formable Areas on Protein Surfaces
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Three-Dimensional CH/π and CH/N Interactions from Quantum-Mechanical and Database Analyses
inferred← citeshttps://doi.org/10.1021/ci034110bopenalex-snapshot
Spectroscopic QSAR Methods and Self-Organizing Molecular Field Analysis for Relating Molecular Structure and Estrogenic Activity
inferred← citeshttps://doi.org/10.1021/cr900238dopenalex-snapshot
Quantitative Correlation of Physical and Chemical Properties with Chemical Structure: Utility for Prediction
inferred← citeshttps://doi.org/10.1021/es050017nopenalex-snapshot
Quantitative Structure−Activity Relationship Models for Prediction of the Toxicity of Polybrominated Diphenyl Ether Congeners
inferred← citeshttps://doi.org/10.1021/tx700362uopenalex-snapshot
Decabromobiphenyl (PBB-209) Activates the Aryl Hydrocarbon Receptor While Decachlorobiphenyl (PCB-209) Is Inactive: Experimental Evidence and Computational Rationalization of the Different Behavior of Some Halogenated Biphenyls
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Profiling the interaction mechanism of indole-based derivatives targeting the HIV-1 gp120 receptor
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