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Quantitative Structure−Activity Relationship Analysis of Functionalized Amino Acid Anticonvulsant Agents Using k Nearest Neighbor and Simulated Annealing PLS Methods
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Anticonvulsant Properties ofN‐Substituted α,α‐Diamino Acid Derivatives
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Molecular Connectivity in Chemistry and Drug Research
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In silico studies for the rational discovery of anticonvulsant compounds
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Functionalized amino acid anticonvulsants: synthesis and pharmacological evaluation of conformationally restricted analogues
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A computational quantitative structure-activity relationship study of carbamate anticonvulsants using quantum pharmacological methods
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Novel Variable Selection Quantitative Structure−Property Relationship Approach Based on the k -Nearest-Neighbor Principle
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Characterization of molecular branching
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Importance of nonbonded attraction in the stereochemistry of the SN2' reaction
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Synthesis and Anticonvulsant Activities of .alpha.-Acetamido-N-benzylacetamide Derivatives Containing an Electron-Deficient .alpha.-Heteroaromatic Substituent
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inferredcites →https://doi.org/10.1021/jm00112a020openalex-snapshot
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inferredcites →https://doi.org/10.1021/jm00165a007openalex-snapshot
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2D and 3D QSAR Analysis of Some Valproic Acid Metabolites and Analogues as Anticonvulsant Agents
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Comparison of Carbamazepine, Phenobarbital, Phenytoin, and Primidone in Partial and Secondarily Generalized Tonic–Clonic Seizures
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Genetics and Epilepsy: A Model from Critical Path Analysis
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Quantum Pharmacologic Studies Applicable to the Design of Anticonvulsants: Theoretical Conformational Analysis and Structure‐Activity Studies of Barbiturates
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Identification of the Descriptor Pharmacophores Using Variable Selection QSAR Applications to Database Mining
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A Novel Two-Step Hierarchical Quantitative Structure–Activity Relationship Modeling Work Flow for Predicting Acute Toxicity of Chemicals in Rodents
inferred← citeshttps://doi.org/10.1289/ehp.1002476openalex-snapshot
Use of in Vitro HTS-Derived Concentration–Response Data as Biological Descriptors Improves the Accuracy of QSAR Models of in Vivo Toxicity
inferred← citeshttps://doi.org/10.1289/ehp.10573openalex-snapshot
Use of Cell Viability Assay Data Improves the Prediction Accuracy of Conventional Quantitative Structure–Activity Relationship Models of Animal Carcinogenicity
inferred← citeshttps://doi.org/10.1371/journal.pone.0000428openalex-snapshot
Combinatorial Computational Approaches to Identify Tetracycline Derivatives as Flavivirus Inhibitors
inferred← citeshttps://doi.org/10.1504/ijcbdd.2011.041415openalex-snapshot
LigSeeSVM: Ligand-based virtual Screening using Support Vector Machines and data fusion
inferred← citeshttps://doi.org/10.1517/17460441.2015.968123openalex-snapshot
QSAR and 3D-QSAR studies applied to compounds with anticonvulsant activity
inferred← citeshttps://doi.org/10.15406/mojddt.2018.02.00039openalex-snapshot
In silico Identification of potential 5α‒reductase inhibitors for prostatic diseases: QSAR modelling, molecular docking, and pre ADME predictions
inferred← citeshttps://doi.org/10.17615/g3gq-9f55openalex-snapshot
Classifier Design to Improve Pattern Classification and Knowledge Discovery for Imbalanced Datasets
inferred← citeshttps://doi.org/10.17615/w4vm-f755openalex-snapshot
The QSARome of the receptorome: Quantitative structure-activity relationship modeling of multiple ligand sets acting at multiple receptors
inferred← citeshttps://doi.org/10.17615/xtc7-2969openalex-snapshot
In silico strategies to study polypharmacology of G-protein-coupled receptors
inferred← citeshttps://doi.org/10.17615/y3bk-qg43openalex-snapshot
New tylophorine analogs as potential antitumor agents
inferred← citeshttps://doi.org/10.18540/jcecvl5iss1pp0049-0062openalex-snapshot
IN-SILICO STUDY FOR PREDICTING THE INHIBITION CONCENTRATION OF SOME HETEROCYCLIC AND PHENYLIC COMPOUNDS AS POTENT HERBICIDES USING THE MLR - GFA APPROACH
inferred← citeshttps://doi.org/10.20450/mjcce.2016.848openalex-snapshot
A simple 2D-QSPR model for the prediction of Setschenow constants of organic compounds
inferred← citeshttps://doi.org/10.2174/0115734064247526231129080415openalex-snapshot
Structure-Activity Relationship Studies on VEGFR2 Tyrosine Kinase Inhibitors for Identification of Potential Natural Anticancer Compounds
inferred← citeshttps://doi.org/10.2174/1568026622666220324151808openalex-snapshot
Synthesis, Molecular Docking, and 2D-QSAR Modeling of Quinoxaline Derivatives as Potent Anticancer Agents against Triple-negative Breast Cancer
inferred← citeshttps://doi.org/10.2174/1570163820666230222151558openalex-snapshot
Assessment of Structural Basis for Thiazolopyridine Derivatives as DNA Gyrase-B Inhibitors
inferred← citeshttps://doi.org/10.2174/1570180819666220509103648openalex-snapshot
QSAR Analysis, Molecular Docking and ADME Studies of Thiobarbituric Acid Derivatives as Thymidine Phosphorylase Inhibitors: A Rational Approach to Anticancer Drug Design by in silico Modelling
inferred← citeshttps://doi.org/10.2174/157340611795564213openalex-snapshot
A Comparative QSAR Analysis of Quinazoline Analogues as Tyrosine Kinase (erbB-2) Inhibitors
inferred← citeshttps://doi.org/10.2174/1574893618666230316122534openalex-snapshot
Exploring the Hepatotoxicity of Drugs through Machine Learning and Network Toxicological Methods
inferred← citeshttps://doi.org/10.22270/jddt.v2i2.118openalex-snapshot
RATIONAL DESIGN OF ANTIBACTERIAL THIENOPYRIMIDINES BY 2D-QSAR STUDY
inferred← citeshttps://doi.org/10.3390/ijms23042105openalex-snapshot
VenomPred: A Machine Learning Based Platform for Molecular Toxicity Predictions
inferred← citeshttps://doi.org/10.3390/ijms27021050openalex-snapshot
In Silico Development of Novel Quinazoline-Based EGFR Inhibitors via 3D-QSAR, Docking, ADMET, and Molecular Dynamics
inferred← citeshttps://doi.org/10.36468/pharmaceutical-sciences.1010openalex-snapshot
Discovery of Novel Tetrahydropyrido-Pyrazole based Cathepsin S Inhibitors: Implications of Two Dimensional Quantitative Structure Activity Relationship Analysis
inferred← citeshttps://doi.org/10.3923/ajdd.2011.85.104openalex-snapshot
Quantitative Structure Activity Relationship Analysis of N-(mercaptoalkanoyl)- and [(acylthio)alkanoyl] Glycine Derivatives as ACE Inhibitors
inferred← citeshttps://doi.org/10.4172/jtco.1000124openalex-snapshot
3D QSAR Analysis on Isatin Derivatives as Carboxyl Esterase Inhibitors Using K-Nearest Neighbor Molecular Field Analysis
inferred← citeshttps://doi.org/10.5012/bkcs.2011.32.7.2397openalex-snapshot
Development of kNN QSAR Models for 3-Arylisoquinoline Antitumor Agents
inferred← citeshttps://doi.org/10.53879/id.54.06.10947openalex-snapshot
DEVELOPMENT OF A ROBUST QSAR MODEL OF ANGIOTENSIN RECEPTOR REVEALS A K NEAREST NEIGHBOR APPLICABLE TO DIVERSE SCAFFOLDS
inferred← citeshttps://doi.org/10.53879/id.60.02.13405openalex-snapshot
2D QSAR ANALYSIS OF CARBONITRILE BASED INHIBITORS OF CATHEPSIN S AS POTENTIAL ANTIRHEUMATIC AGENTS
inferred← citeshttps://doi.org/10.5582/ddt.2012.v6.2.69openalex-snapshot
In silico ligand based design of indolylpiperidinyl derivatives as novel histamine H1 receptor antagonists
inferred← citeshttps://doi.org/10.6084/m9.figshare.17088152openalex-snapshot
Additional file 1 of Chemical toxicity prediction based on semi-supervised learning and graph convolutional neural network
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.