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Quantitative Structure–Activity Relationship Models That Stand the Test of Time
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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/minf.201000160openalex-snapshot
Predictivity of Simulated ADME AutoQSAR Models over Time
inferredcites →https://doi.org/10.1002/minf.201100107openalex-snapshot
Automated QSAR with a Hierarchy of Global and Local Models
inferredcites →https://doi.org/10.1002/series6138openalex-snapshot
Methods and Principles in Medicinal Chemistry
inferredcites →https://doi.org/10.1007/s10822-005-9029-8openalex-snapshot
Automated QSPR through Competitive Workflow
inferredcites →https://doi.org/10.1007/s10822-006-9095-6openalex-snapshot
Development, interpretation and temporal evaluation of a global QSAR of hERG electrophysiology screening data
inferredcites →https://doi.org/10.1016/j.drudis.2012.03.003openalex-snapshot
Better compounds faster: the development and exploitation of a desktop predictive chemistry toolkit
inferredcites →https://doi.org/10.1016/j.ijpharm.2006.06.001openalex-snapshot
On the misinterpretation of the correlation coefficient in pharmaceutical sciences
inferredcites →https://doi.org/10.1021/ci010363yopenalex-snapshot
Search for Predictive Generic Model of Aqueous Solubility Using Bayesian Neural Nets
inferredcites →https://doi.org/10.1021/ci060113nopenalex-snapshot
An Improved Approximation to the Estimation of the Critical F Values in Best Subset Regression
inferredcites →https://doi.org/10.1023/a:1025358319677openalex-snapshot
In silico ADME/Tox: why models fail
inferredcites →https://doi.org/10.1038/nrd1470openalex-snapshot
Can the pharmaceutical industry reduce attrition rates?
inferredcites →https://doi.org/10.1038/nrd3552openalex-snapshot
The influence of the 'organizational factor' on compound quality in drug discovery
inferredcites →https://doi.org/10.1136/oem.49.7.526-aopenalex-snapshot
A cautionary note on the use of the correlation coefficient.
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/minf.201900059openalex-snapshot
Investigation of Factors Affecting the Performance of in silico Volume Distribution QSAR Models for Human, Rat, Mouse, Dog & Monkey
inferred← citeshttps://doi.org/10.1007/s10822-013-9648-4openalex-snapshot
QSAR workbench: automating QSAR modeling to drive compound design
inferred← citeshttps://doi.org/10.1007/s10822-017-0039-0openalex-snapshot
Development of a pharmacophore for cruzain using oxadiazoles as virtual molecular probes: quantitative structure–activity relationship studies
inferred← citeshttps://doi.org/10.1007/s12272-015-0640-5openalex-snapshot
Role of computer-aided drug design in modern drug discovery
inferred← citeshttps://doi.org/10.1007/s13738-019-01726-yopenalex-snapshot
Studies of febuxostat analogues as xanthine oxidase inhibitors through 3D-QSAR, Topomer CoMFA and molecular modeling
inferred← citeshttps://doi.org/10.1016/b978-0-12-409547-2.02586-5openalex-snapshot
The Why and How of Absorption, Distribution, Metabolism, Excretion, and Toxicity Research
inferred← citeshttps://doi.org/10.1016/b978-0-12-409547-2.12348-0openalex-snapshot
Quantitative Structure–Activity Relationships
inferred← citeshttps://doi.org/10.1016/b978-0-12-801238-3.11532-6openalex-snapshot
In Silico ADME Modeling
inferred← citeshttps://doi.org/10.1016/j.bmcl.2016.08.072openalex-snapshot
Evolution of physicochemical properties of melanin concentrating hormone receptor 1 (MCHr1) antagonists
inferred← citeshttps://doi.org/10.1016/j.jtice.2016.09.018openalex-snapshot
Molecular modelling studies of 3,5-dipyridyl-1,2,4-triazole derivatives as xanthine oxidoreductase inhibitors using 3D-QSAR, Topomer CoMFA, molecular docking and molecular dynamic simulations
inferred← citeshttps://doi.org/10.1021/acs.jcim.0c00678openalex-snapshot
Nearest Neighbor Gaussian Process for Quantitative Structure–Activity Relationships
inferred← citeshttps://doi.org/10.1021/acs.jcim.2c00245openalex-snapshot
Exploring Deep Learning of Quantum Chemical Properties for Absorption, Distribution, Metabolism, and Excretion Predictions
inferred← citeshttps://doi.org/10.1021/acs.jcim.2c00699openalex-snapshot
Prediction Accuracy of Production ADMET Models as a Function of Version: Activity Cliffs Rule
inferred← citeshttps://doi.org/10.1021/acs.jcim.2c00803openalex-snapshot
Stability of Prediction in Production ADMET Models as a Function of Version: Why and When Predictions Change
inferred← citeshttps://doi.org/10.1021/acs.jcim.8b00626openalex-snapshot
De Novo Molecule Design by Translating from Reduced Graphs to SMILES
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b01067openalex-snapshot
Experimental Error, Kurtosis, Activity Cliffs, and Methodology: What Limits the Predictivity of Quantitative Structure–Activity Relationship Models?
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.5b01654openalex-snapshot
Discovery of (3-(4-(2-Oxa-6-azaspiro[3.3]heptan-6-ylmethyl)phenoxy)azetidin-1-yl)(5-(4-methoxyphenyl)-1,3,4-oxadiazol-2-yl)methanone (AZD1979), a Melanin Concentrating Hormone Receptor 1 (MCHr1) Antagonist with Favorable Physicochemical Properties
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.7b00861openalex-snapshot
Structure–Affinity Relationships and Structure–Kinetic Relationships of 1,2-Diarylimidazol-4-carboxamide Derivatives as Human Cannabinoid 1 Receptor Antagonists
inferred← citeshttps://doi.org/10.1021/acs.molpharmaceut.6b01059openalex-snapshot
In Vitro Intrinsic Permeability: A Transporter-Independent Measure of Caco-2 Cell Permeability in Drug Design and Development
inferred← citeshttps://doi.org/10.1021/ci500084wopenalex-snapshot
Global Quantitative Structure–Activity Relationship Models vs Selected Local Models as Predictors of Off-Target Activities for Project Compounds
inferred← citeshttps://doi.org/10.1039/9781839160745-00039openalex-snapshot
Computational Methods for the Discovery of Chemical Probes
inferred← citeshttps://doi.org/10.1517/17460441.2015.1043885openalex-snapshot
In silicotools used for compound selection during target-based drug discovery and development
inferred← citeshttps://doi.org/10.4155/fmc-2017-0170openalex-snapshot
On the Virtues of Automated Quantitative Structure–Activity Relationship: The New Kid on the Block
inferred← citeshttps://doi.org/10.5599/admet.6.1.470openalex-snapshot
In silico ADME in drug design – enhancing the impact
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