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Beware of R 2: Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models

Journal of chemical information and modeling, 2015-07, Vol.55 (7), p.1316-1322

2015

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Beware of R(2): Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models

Journal of chemical information and modeling, 2015-07, Vol.55 (7), p.1316-1322

2015

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Beware of R2: simple, unambiguous assessment of the prediction accuracy of QSAR and QSPR models

Journal of chemical information and modeling, 2015-07, Vol.55 (7), p.1316-1322

2015

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Beware of R^sup 2^: Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models

Journal of chemical information and modeling, 2015-07, Vol.55 (7), p.1316

2015

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kappa Nearest neighbors QSAR modeling as a variational problem: theory and applications

Journal of chemical information and modeling, 2005-05, Vol.45 (3), p.777-785

2005

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Chemometric Analysis of Ligand Receptor Complementarity: Identifying Complementary Ligands Based on Receptor Information (CoLiBRI)

Journal of chemical information and modeling, 2006-03, Vol.46 (2), p.844-851

2006

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Combinatorial QSAR of Ambergris Fragrance Compounds

Journal of Chemical Information and Computer Sciences, 2004-03, Vol.44 (2), p.582-595

2004

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Trust, but Verify II: A Practical Guide to Chemogenomics Data Curation

Journal of chemical information and modeling, 2016-07, Vol.56 (7), p.1243-1252

2016

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Trust, But Verify: On the Importance of Chemical Structure Curation in Cheminformatics and QSAR Modeling Research

Journal of chemical information and modeling, 2010-07, Vol.50 (7), p.1189-1204

2010

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Phantom PAINS: Problems with the Utility of Alerts for P an- A ssay IN terference Compound S

Journal of chemical information and modeling, 2017-03, Vol.57 (3), p.417-427

2017

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Materials Informatics

Journal of chemical information and modeling, 2018-12, Vol.58 (12), p.2377-2379

2018

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OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug Design

Journal of chemical information and modeling, 2021-01, Vol.61 (1), p.7-13

2021

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Materials Informatics

Journal of chemical information and modeling, 2018-07, Vol.58 (7), p.1313-1314

2018

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Phantom PAINS: Problems with the Utility of Alerts for Pan‑Assay INterference CompoundS

Journal of chemical information and modeling, 2017-03, Vol.57 (3), p.417-427

2017

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Data Set Modelability by QSAR

Journal of chemical information and modeling, 2014-01, Vol.54 (1), p.1-4

2014

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Does Rational Selection of Training and Test Sets Improve the Outcome of QSAR Modeling?

Journal of chemical information and modeling, 2012-10, Vol.52 (10), p.2570-2578

2012

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A Novel Automated Lazy Learning QSAR (ALL-QSAR) Approach: Method Development, Applications, and Virtual Screening of Chemical Databases Using Validated ALL-QSAR Models

Journal of chemical information and modeling, 2006-09, Vol.46 (5), p.1984-1995

2006

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Critical Assessment of QSAR Models of Environmental Toxicity against Tetrahymena pyriformis: Focusing on Applicability Domain and Overfitting by Variable Selection

Journal of Chemical Information and Modeling, 2008-09, Vol.48 (9), p.1733-1746

2008

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Multi-Descriptor Read Across (MuDRA): A Simple and Transparent Approach for Developing Accurate Quantitative Structure–Activity Relationship Models

Journal of chemical information and modeling, 2018-06, Vol.58 (6), p.1214-1223

2018

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Joint Virtual Special Issue on Computational Toxicology

Journal of chemical information and modeling, 2020-03, Vol.60 (3), p.1069-1071

2020

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ROBOKOP KG and KGB: Integrated Knowledge Graphs from Federated Sources

Journal of chemical information and modeling, 2019-12, Vol.59 (12), p.4968-4973

2019

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BigBind: Learning from Nonstructural Data for Structure-Based Virtual Screening

Journal of chemical information and modeling, 2024-04, Vol.64 (7), p.2488-2495

2024

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Combinatorial QSAR Modeling of Chemical Toxicants Tested against Tetrahymena pyriformis

Journal of chemical information and computer sciences, 2008-04, Vol.48 (4), p.766-784

2008

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Target-Specific Native/Decoy Pose Classifier Improves the Accuracy of Ligand Ranking in the CSAR 2013 Benchmark

Journal of chemical information and modeling, 2015-01, Vol.55 (1), p.63-71

2015

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Large-Scale Modeling of Multispecies Acute Toxicity End Points Using Consensus of Multitask Deep Learning Methods

Journal of chemical information and modeling, 2021-02, Vol.61 (2), p.653-663

2021

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Beware of R 2: Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models

Beware of R(2): Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models

Beware of R2: simple, unambiguous assessment of the prediction accuracy of QSAR and QSPR models

Beware of R^sup 2^: Simple, Unambiguous Assessment of the Prediction Accuracy of QSAR and QSPR Models

kappa Nearest neighbors QSAR modeling as a variational problem: theory and applications

Chemometric Analysis of Ligand Receptor Complementarity: Identifying Complementary Ligands Based on Receptor Information (CoLiBRI)

Combinatorial QSAR of Ambergris Fragrance Compounds

Trust, but Verify II: A Practical Guide to Chemogenomics Data Curation

Trust, But Verify: On the Importance of Chemical Structure Curation in Cheminformatics and QSAR Modeling Research

Phantom PAINS: Problems with the Utility of Alerts for P an- A ssay IN terference Compound S

Materials Informatics

OpenChem: A Deep Learning Toolkit for Computational Chemistry and Drug Design

Materials Informatics

Phantom PAINS: Problems with the Utility of Alerts for Pan‑Assay INterference CompoundS

Data Set Modelability by QSAR

Does Rational Selection of Training and Test Sets Improve the Outcome of QSAR Modeling?

A Novel Automated Lazy Learning QSAR (ALL-QSAR) Approach: Method Development, Applications, and Virtual Screening of Chemical Databases Using Validated ALL-QSAR Models

Critical Assessment of QSAR Models of Environmental Toxicity against Tetrahymena pyriformis: Focusing on Applicability Domain and Overfitting by Variable Selection

Multi-Descriptor Read Across (MuDRA): A Simple and Transparent Approach for Developing Accurate Quantitative Structure–Activity Relationship Models

Joint Virtual Special Issue on Computational Toxicology

ROBOKOP KG and KGB: Integrated Knowledge Graphs from Federated Sources

BigBind: Learning from Nonstructural Data for Structure-Based Virtual Screening

Combinatorial QSAR Modeling of Chemical Toxicants Tested against Tetrahymena pyriformis

Target-Specific Native/Decoy Pose Classifier Improves the Accuracy of Ligand Ranking in the CSAR 2013 Benchmark

Large-Scale Modeling of Multispecies Acute Toxicity End Points Using Consensus of Multitask Deep Learning Methods

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