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Similarity to Molecules in the Training Set Is a Good Discriminator for Prediction Accuracy in QSAR
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Outgoing claims: the papers this work cites, builds on, or argues with.
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New molecular descriptors for 2D and 3D structures. Theory
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The Centroid Approximation for Mixtures: Calculating Similarity and Deriving Structure−Activity Relationships
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Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling
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Neighborhood Behavior: A Useful Concept for Validation of “Molecular Diversity” Descriptors
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Introduction to Linear Regression Analysis
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Ligand Conformational Variability Enhances Machine Learning Prediction of Protein–Ligand Binding Affinity
inferred← citeshttps://doi.org/10.1021/acs.molpharmaceut.5b00119openalex-snapshot
Major Source of Error in QSPR Prediction of Intrinsic Thermodynamic Solubility of Drugs: Solid vs Nonsolid State Contributions?
inferred← citeshttps://doi.org/10.1021/acsami.2c19391openalex-snapshot
Data-Driven Discovery of Graphene-Based Dual-Atom Catalysts for Hydrogen Evolution Reaction with Graph Neural Network and DFT Calculations
inferred← citeshttps://doi.org/10.1021/acsomega.1c05512openalex-snapshot
Impact of Artificial Intelligence on Compound Discovery, Design, and Synthesis
inferred← citeshttps://doi.org/10.1021/acsomega.5c11875openalex-snapshot
Explicit Applicability Domain Calculations Can Help Determine When Uncertainty Estimates Are Less Reliable
inferred← citeshttps://doi.org/10.1021/acsomega.8b01647openalex-snapshot
How Precise Are Our Quantitative Structure–Activity Relationship Derived Predictions for New Query Chemicals?
inferred← citeshttps://doi.org/10.1021/bk-2016-1222.ch006openalex-snapshot
Molecular Similarity Approaches in Chemoinformatics: Early History and Literature Status
inferred← citeshttps://doi.org/10.1021/ci0500381openalex-snapshot
A Stepwise Approach for Defining the Applicability Domain of SAR and QSAR Models
inferred← citeshttps://doi.org/10.1021/ci050225zopenalex-snapshot
Lead Validation and SAR Development via Chemical Similarity Searching; Application to Compounds Targeting the pY+3 Site of the SH2 Domain of p56lck
inferred← citeshttps://doi.org/10.1021/ci050308fopenalex-snapshot
Development and Evaluation of an in Silico Model for hERG Binding
inferred← citeshttps://doi.org/10.1021/ci050413popenalex-snapshot
QSAR − How Good Is It in Practice? Comparison of Descriptor Sets on an Unbiased Cross Section of Corporate Data Sets
inferred← citeshttps://doi.org/10.1021/ci0504521openalex-snapshot
Designing Novel Polymers with Targeted Properties Using the Signature Molecular Descriptor
inferred← citeshttps://doi.org/10.1021/ci050519kopenalex-snapshot
Assessing Different Classification Methods for Virtual Screening
inferred← citeshttps://doi.org/10.1021/ci060164kopenalex-snapshot
Random Forest Models To Predict Aqueous Solubility
inferred← citeshttps://doi.org/10.1021/ci100253ropenalex-snapshot
Applicability Domains for Classification Problems: Benchmarking of Distance to Models for Ames Mutagenicity Set
inferred← citeshttps://doi.org/10.1021/ci100270xopenalex-snapshot
Capturing Structure−Activity Relationships from Chemogenomic Spaces
inferred← citeshttps://doi.org/10.1021/ci200472sopenalex-snapshot
Improving Classical Substructure-Based Virtual Screening to Handle Extrapolation Challenges
inferred← citeshttps://doi.org/10.1021/ci200615hopenalex-snapshot
Comparison of Random Forest and Pipeline Pilot Naïve Bayes in Prospective QSAR Predictions
inferred← citeshttps://doi.org/10.1021/ci300004nopenalex-snapshot
Three Useful Dimensions for Domain Applicability in QSAR Models Using Random Forest
inferred← citeshttps://doi.org/10.1021/ci3001748openalex-snapshot
Lattice Enumeration for Inverse Molecular Design Using the Signature Descriptor
inferred← citeshttps://doi.org/10.1021/ci300554topenalex-snapshot
Interpretable, Probability-Based Confidence Metric for Continuous Quantitative Structure–Activity Relationship Models
inferred← citeshttps://doi.org/10.1021/ci400084kopenalex-snapshot
Time-Split Cross-Validation as a Method for Estimating the Goodness of Prospective Prediction.
inferred← citeshttps://doi.org/10.1021/ci400250copenalex-snapshot
Kernel-Based Partial Least Squares: Application to Fingerprint-Based QSAR with Model Visualization
inferred← citeshttps://doi.org/10.1021/ci400482eopenalex-snapshot
Using Random Forest To Model the Domain Applicability of Another Random Forest Model
inferred← citeshttps://doi.org/10.1021/ci4006595openalex-snapshot
Assessment of Machine Learning Reliability Methods for Quantifying the Applicability Domain of QSAR Regression Models
inferred← citeshttps://doi.org/10.1021/ci500016vopenalex-snapshot
Merging Applicability Domains for in Silico Assessment of Chemical Mutagenicity
inferred← citeshttps://doi.org/10.1021/ci7004065openalex-snapshot
Definition and Detection of Outliers in Chemical Space
inferred← citeshttps://doi.org/10.1021/ci8001233openalex-snapshot
Efficient Calculation of Molecular Properties from Simulation Using Kernel Molecular Dynamics
inferred← citeshttps://doi.org/10.1021/ci8001414openalex-snapshot
Assessing How Well a Modeling Protocol Captures a Structure−Activity Landscape
inferred← citeshttps://doi.org/10.1021/ci800151mopenalex-snapshot
Critical Assessment of QSAR Models of Environmental Toxicity against Tetrahymena pyriformis: Focusing on Applicability Domain and Overfitting by Variable Selection
inferred← citeshttps://doi.org/10.1021/ci800164uopenalex-snapshot
Practical Outcomes of Applying Ensemble Machine Learning Classifiers to High-Throughput Screening (HTS) Data Analysis and Screening
inferred← citeshttps://doi.org/10.1021/ci800253uopenalex-snapshot
External Validation and Prediction Employing the Predictive Squared Correlation Coefficient — Test Set Activity Mean vs Training Set Activity Mean
inferred← citeshttps://doi.org/10.1021/ci800302gopenalex-snapshot
Analysis of Neighborhood Behavior in Lead Optimization and Array Design
inferred← citeshttps://doi.org/10.1021/ci9000579openalex-snapshot
Predicting the Predictability: A Unified Approach to the Applicability Domain Problem of QSAR Models
inferred← citeshttps://doi.org/10.1021/jm060076ropenalex-snapshot
Insights for Human Ether-a-Go-Go-Related Gene Potassium Channel Inhibition Using Recursive Partitioning and Kohonen and Sammon Mapping Techniques
inferred← citeshttps://doi.org/10.1021/jm060333sopenalex-snapshot
In Silico Prediction of Cytochrome P450 2D6 and 3A4 Inhibition Using Gaussian Kernel Weightedk-Nearest Neighbor and Extended Connectivity Fingerprints, Including Structural Fragment Analysis of Inhibitors versus Noninhibitors
inferred← citeshttps://doi.org/10.1021/mp300555nopenalex-snapshot
Integration of in Silico and in Vitro Tools for Scaffold Optimization during Drug Discovery: Predicting P-Glycoprotein Efflux
inferred← citeshttps://doi.org/10.1021/tx800102eopenalex-snapshot
Machine Learning Methods and Docking for Predicting Human Pregnane X Receptor Activation
inferred← citeshttps://doi.org/10.1038/s41370-020-0238-yopenalex-snapshot
Development and evaluation of a high throughput inhalation model for organic chemicals
inferred← citeshttps://doi.org/10.1038/s41540-024-00374-0openalex-snapshot
DeepARV: ensemble deep learning to predict drug-drug interaction of clinical relevance with antiretroviral therapy
inferred← citeshttps://doi.org/10.1038/s41598-022-19205-5openalex-snapshot
A universal similarity based approach for predictive uncertainty quantification in materials science
inferred← citeshttps://doi.org/10.1038/s42256-020-00236-4openalex-snapshot
Drug discovery with explainable artificial intelligence
inferred← citeshttps://doi.org/10.1038/sj.bjp.0707306openalex-snapshot
In silicopharmacology for drug discovery: applications to targets and beyond
inferred← citeshttps://doi.org/10.1039/9781847558879-00240openalex-snapshot
Early ADME/T Predictions: Toy or Tool?
inferred← citeshttps://doi.org/10.1039/9781849732093-00301openalex-snapshot
Developing the Applicability Domain of In Silico Models: Relevance, Importance and Methods
inferred← citeshttps://doi.org/10.1039/c2ra01345bopenalex-snapshot
Many structurally related drugs bind different targets whereas distinct drugs display significant target overlap
inferred← citeshttps://doi.org/10.1039/c3an01644gopenalex-snapshot
Molecular interactions of nanomaterials and organisms: defining biomarkers for toxicity and high-throughput screening using traditional and next-generation sequencing approaches
inferred← citeshttps://doi.org/10.1039/c9sc00616hopenalex-snapshot
Bayesian semi-supervised learning for uncertainty-calibrated prediction of molecular properties and active learning
inferred← citeshttps://doi.org/10.1039/d0sc00129eopenalex-snapshot
Molecular dynamics based descriptors for predicting supramolecular gelation
inferred← citeshttps://doi.org/10.1039/d4dd00089gopenalex-snapshot
Linear graphlet models for accurate and interpretable cheminformatics
inferred← citeshttps://doi.org/10.1039/d5ta06120bopenalex-snapshot
Orchestrating explainable AI, ChatGPT, and human expertise: a framework for extracting polymer design guidelines
inferred← citeshttps://doi.org/10.1039/d6ra05786aopenalex-snapshot
From QSAR to deep learning: an interpretable comprehensive pipeline with a read-across approach for mutagenicity prediction via the Enalos Cloud Platform
inferred← citeshttps://doi.org/10.1063/5.0157644openalex-snapshot
Discovery of structure–property relations for molecules via hypothesis-driven active learning over the chemical space
inferred← citeshttps://doi.org/10.1080/00498250701646341openalex-snapshot
Future directions for drug transporter modelling
inferred← citeshttps://doi.org/10.1080/10629360601053984openalex-snapshot
The quality of QSAR models: problems and solutions
inferred← citeshttps://doi.org/10.1080/1062936x.2013.781537openalex-snapshot
Assessment of hydroxylated metabolites of polychlorinated biphenyls as potential xenoestrogens: a QSAR comparative analysis∗
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