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Comparison of Random Forest and Pipeline Pilot Naïve Bayes in Prospective QSAR Predictions
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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.200510161openalex-snapshot
On Selection of Training and Test Sets for the Development of Predictive QSAR models
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Analysis and use of fragment-occurrence data in similarity-based virtual screening
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PLS-regression: a basic tool of chemometrics
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Retro-RegressionAnother Important Multivariate Regression Improvement
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Atom pairs as molecular features in structure-activity studies: definition and applications
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Topological torsion: a new molecular descriptor for SAR applications. Comparison with other descriptors
inferredcites →https://doi.org/10.1021/ci020039iopenalex-snapshot
QSAR/QSPR Studies Using Probabilistic Neural Networks and Generalized Regression Neural Networks
inferredcites →https://doi.org/10.1021/ci0203702openalex-snapshot
On the Use of Neural Network Ensembles in QSAR and QSPR
inferredcites →https://doi.org/10.1021/ci025620topenalex-snapshot
Active Learning with Support Vector Machines in the Drug Discovery Process
inferredcites →https://doi.org/10.1021/ci034160gopenalex-snapshot
Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling
inferredcites →https://doi.org/10.1021/ci049782wopenalex-snapshot
Similarity to Molecules in the Training Set Is a Good Discriminator for Prediction Accuracy in QSAR
inferredcites →https://doi.org/10.1021/ci0500379openalex-snapshot
Boosting: An Ensemble Learning Tool for Compound Classification and QSAR Modeling
inferredcites →https://doi.org/10.1021/ci060003gopenalex-snapshot
Prediction of Biological Targets for Compounds Using Multiple-Category Bayesian Models Trained on Chemogenomics Databases
inferredcites →https://doi.org/10.1021/ci0601315openalex-snapshot
Improved Naïve Bayesian Modeling of Numerical Data for Absorption, Distribution, Metabolism and Excretion (ADME) Property Prediction
inferredcites →https://doi.org/10.1021/ci100072zopenalex-snapshot
Pharmaceutical Perspectives of Nonlinear QSAR Strategies
inferredcites →https://doi.org/10.1021/ci200199uopenalex-snapshot
Large-Scale Similarity Search Profiling of ChEMBL Compound Data Sets
inferredcites →https://doi.org/10.1021/ci600332jopenalex-snapshot
Contemporary QSAR Classifiers Compared
inferredcites →https://doi.org/10.1021/ci700245fopenalex-snapshot
Development of a New Regression Analysis Method Using Independent Component Analysis
inferredcites →https://doi.org/10.1021/ci700333topenalex-snapshot
Bayesian Similarity Searching in High-Dimensional Descriptor Spaces Combined with Kullback-Leibler Descriptor Divergence Analysis
inferredcites →https://doi.org/10.1021/ci700380xopenalex-snapshot
Alternative Global Goodness Metrics and Sensitivity Analysis: Heuristics to Check the Robustness of Conclusions from Studies Comparing Virtual Screening Methods
inferredcites →https://doi.org/10.1021/ci800143nopenalex-snapshot
Global Bayesian Models for the Prioritization of Antitubercular Agents
inferredcites →https://doi.org/10.1021/ci800249sopenalex-snapshot
How Similar Are Similarity Searching Methods? A Principal Component Analysis of Molecular Descriptor Space
inferredcites →https://doi.org/10.1021/ci900406xopenalex-snapshot
Gaussian Processes for Classification: QSAR Modeling of ADMET and Target Activity
inferredcites →https://doi.org/10.1021/ci950274jopenalex-snapshot
Chemical Similarity Using Physiochemical Property Descriptors
inferredcites →https://doi.org/10.1021/jm0303195openalex-snapshot
Classification of Kinase Inhibitors Using a Bayesian Model
inferredcites →https://doi.org/10.1021/jm030408hopenalex-snapshot
Prediction of Human Volume of Distribution Values for Neutral and Basic Drugs. 2. Extended Data Set and Leave-Class-Out Statistics
inferredcites →https://doi.org/10.1021/jm049111popenalex-snapshot
Judging the Significance of Multiple Linear Regression Models
inferredcites →https://doi.org/10.1021/jm980697nopenalex-snapshot
Robust QSAR Models Using Bayesian Regularized Neural Networks
inferredcites →https://doi.org/10.1023/a:1020869118689openalex-snapshot
Predictive QSAR modeling based on diversity sampling of experimental datasets for the training and test set selection
inferredcites →https://doi.org/10.1038/nbt1228openalex-snapshot
Global mapping of pharmacological space
inferredcites →https://doi.org/10.1039/b409865jopenalex-snapshot
Comparison of topological descriptors for similarity-based virtual screening using multiple bioactive reference structures
inferredcites →https://doi.org/10.1080/00401706.1999.10485951openalex-snapshot
Statistical Learning Theory
inferredcites →https://doi.org/10.1177/1087057103260590openalex-snapshot
Enrichment of Extremely Noisy High-Throughput Screening Data Using a Naïve Bayes Classifier
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Using Extended-Connectivity Fingerprints with Laplacian-Modified Bayesian Analysis in High-Throughput Screening Follow-Up
inferredcites →https://doi.org/10.1517/17460441.2010.492827openalex-snapshot
Advances in computational methods to predict the biological activity of compounds
inferredcites →https://doi.org/10.2174/156802610791111506openalex-snapshot
QSAR in the Pharmaceutical Research Setting: QSAR Models for Broad, Large Problems
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Additional file 1 of Large-scale comparison of machine learning methods for profiling prediction of kinase inhibitors
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Additional file 2 of Large-scale comparison of machine learning methods for profiling prediction of kinase inhibitors
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Estimation de l'écotoxicité de substances chimiques par des méthodes à noyaux
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