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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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Materials Informatics: Methods, Tools, and Applications

1, 2019

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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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Chemoinformatics approaches to virtual screening

1, 2008

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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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ON THE ROLE OF INFECTION IN ALZHEIMER’S DISEASE (AD): HERPES VIRUSES ARE ASSOCIATED WITH SIGNIFICANT INCREASE IN AD RISK IN A LARGE POPULATION-REPRESENTATIVE SAMPLE OF ELDERLY INDIVIDUALS

Alzheimer's & dementia, 2017-07, Vol.13 (7), p.P1423-P1424

2017

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Use of Cell Viability Assay Data Improves the Prediction Accuracy of Conventional Quantitative Structure-Activity Relationship Models of Animal Carcinogenicity

Environmental health perspectives, 2008-04, Vol.116 (4), p.506-513

2008

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4.07 - Predictive Quantitative Structure–Activity Relationship Modeling

Comprehensive Medicinal Chemistry II, 2007, Vol.4, p.149-165

Tropsha, A.

Second Edition, 2007

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HiT QSAR Study of Antivirals’ Bioavailability

Antiviral research, 2009-05, Vol.82 (2), p.A56-A56

2009

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Rational design of a three‐heptad coiled‐coil protein and comparison by molecular dynamics simulation with the GCN4 coiled coil: Presence of interior three‐center hydrogen bonds

Protein science, 1994-02, Vol.3 (2), p.345-355

1994

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Automated Computation of Materials Properties

Materials Informatics, 2019

2019

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Cognitive Chemistry: The Marriage of Machine Learning and Chemistry to Accelerate Materials Discovery

Materials Informatics, 2019

2019

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Crystallography Open Database: History, Development, and Perspectives

Materials Informatics, 2019

2019

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From Topological Descriptors to Expert Systems: A Route to Predictable Materials

Materials Informatics, 2019

2019

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Machine Learning Interatomic Potentials for Global Optimization and Molecular Dynamics Simulation

Materials Informatics, 2019

2019

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A High‐Throughput Computational Study Driven by the AiiDA Materials Informatics Framework and the PAULING FILE as Reference Database

Materials Informatics, 2019

2019

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Modeling Materials Quantum Properties with Machine Learning

Materials Informatics, 2019

2019

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Pauling File: Toward a Holistic View

Materials Informatics, 2019

2019

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The Inorganic Crystal Structure Database (ICSD): A Tool for Materials Sciences

Materials Informatics, 2019

2019

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The "random-coil" state of proteins: Comparison of database statistics and molecular simulations

Proteins, structure, function, and bioinformatics, 1999-09, Vol.36 (4), p.407-418

1999

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Modeling of p38 mitogen-activated protein kinase inhibitors using the Catalyst[sup]TM[[sup] HypoGen and k-nearest neighbor QSAR methods

Journal of molecular graphics & modelling, 2004-10, Vol.23 (2), p.129-138

2004

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Subject Index

Chemoinformatics approaches to virtual screening, 2008

2008

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Chemoinformatics approaches to virtual screening, 2008

2008

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Front Matter

Chemoinformatics approaches to virtual screening, 2008

2008

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Preface

Chemoinformatics approaches to virtual screening, 2008

2008

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Zeitschrift / SerieJournal Of Medicinal Chemistry

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

Materials Informatics: Methods, Tools, and Applications

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

Chemoinformatics approaches to virtual screening

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

ON THE ROLE OF INFECTION IN ALZHEIMER’S DISEASE (AD): HERPES VIRUSES ARE ASSOCIATED WITH SIGNIFICANT INCREASE IN AD RISK IN A LARGE POPULATION-REPRESENTATIVE SAMPLE OF ELDERLY INDIVIDUALS

Use of Cell Viability Assay Data Improves the Prediction Accuracy of Conventional Quantitative Structure-Activity Relationship Models of Animal Carcinogenicity

4.07 - Predictive Quantitative Structure–Activity Relationship Modeling

HiT QSAR Study of Antivirals’ Bioavailability

Rational design of a three‐heptad coiled‐coil protein and comparison by molecular dynamics simulation with the GCN4 coiled coil: Presence of interior three‐center hydrogen bonds

Automated Computation of Materials Properties

Cognitive Chemistry: The Marriage of Machine Learning and Chemistry to Accelerate Materials Discovery

Crystallography Open Database: History, Development, and Perspectives

From Topological Descriptors to Expert Systems: A Route to Predictable Materials

Machine Learning Interatomic Potentials for Global Optimization and Molecular Dynamics Simulation

A High‐Throughput Computational Study Driven by the AiiDA Materials Informatics Framework and the PAULING FILE as Reference Database

Modeling Materials Quantum Properties with Machine Learning

Pauling File: Toward a Holistic View

The Inorganic Crystal Structure Database (ICSD): A Tool for Materials Sciences

The "random-coil" state of proteins: Comparison of database statistics and molecular simulations

Modeling of p38 mitogen-activated protein kinase inhibitors using the Catalyst[sup]TM[[sup] HypoGen and k-nearest neighbor QSAR methods

Subject Index

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Front Matter

Preface

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