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Towards a gold standard: regarding quality in public domain chemistry databases and approaches to improving the situation

Drug discovery today, 2012-07, Vol.17 (13-14), p.685-701

2012

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Identification of “Known Unknowns” Utilizing Accurate Mass Data and ChemSpider

Journal of the American Society for Mass Spectrometry, 2012-01, Vol.23 (1), p.179-185

2012

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Open-source QSAR models for pKa prediction using multiple machine learning approaches

Journal of cheminformatics, 2019-09, Vol.11 (1), p.60-20, Article 60

2019

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Deep Learning Insights into Lanthanides Complexation Chemistry

Molecules (Basel, Switzerland), 2021-05, Vol.26 (11), p.3237

2021

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Free and open-source QSAR-ready workflow for automated standardization of chemical structures in support of QSAR modeling

Journal of cheminformatics, 2024-02, Vol.16 (1), p.19-19, Article 19

2024

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ChemTrove: Enabling a Generic ELN To Support Chemistry through the Use of Transferable Plug-ins and Online Data Sources

Journal of chemical information and modeling, 2015-03, Vol.55 (3), p.501-509

2015

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Graph Convolutional Neural Networks as “General-Purpose” Property Predictors: The Universality and Limits of Applicability

Journal of chemical information and modeling, 2020-01, Vol.60 (1), p.22-28

2020

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Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets

Molecular pharmaceutics, 2017-12, Vol.14 (12), p.4462-4475

2017

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Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining

Journal of cheminformatics, 2010-03, Vol.2 (1), p.3-3, Article 3

2010

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Size Doesn’t Matter: Predicting Physico- or Biochemical Properties Based on Dozens of Molecules

The journal of physical chemistry letters, 2021-09, Vol.12 (38), p.9213-9219

2021

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Transferable and Extensible Machine Learning-Derived Atomic Charges for Modeling Hybrid Nanoporous Materials

Chemistry of materials, 2020-09, Vol.32 (18), p.7822-7831

2020

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Machine-learning-assisted search for functional materials over extended chemical space

Materials horizons, 2020, Vol.7 (1), p.271-2718

2020

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CATMoS: Collaborative Acute Toxicity Modeling Suite

Environmental health perspectives, 2021-04, Vol.129 (4), p.47013

2021

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Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery

Molecular pharmaceutics, 2018-10, Vol.15 (10), p.4346-4360

2018

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Machine Learning Models for Mycobacterium tuberculosis In Vitro Activity: Prediction and Target Visualization

Molecular pharmaceutics, 2022-02, Vol.19 (2), p.674-689

2022

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Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Datasets

Molecular pharmaceutics, 2017-11, Vol.14 (12), p.4462-4475

2017

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ChemSpider - building a foundation for the semantic web by hosting a crowd sourced databasing platform for chemistry

Journal of cheminformatics, 2010-05, Vol.2 (Suppl 1), p.O16-O16, Article O16

2010

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The ChEMBL database as linked open data

Journal of cheminformatics, 2013-05, Vol.5 (1), p.23-23, Article 23

2013

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Correction to “Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery”

Molecular pharmaceutics, 2021-07, Vol.18 (7), p.2833-2833

2021

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Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining

Journal of cheminformatics, 2010-06, Vol.2 (1), p.4-4

2010

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Erratum: CATMoS: Collaborative Acute Toxicity Modeling Suite

Environmental health perspectives, 2021-10, Vol.129 (10), p.109001

2021

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Erratum: CATMoS: Collaborative Acute Toxicity Modeling Suite

Environmental health perspectives, 2021-07, Vol.129 (7)

2021

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The Chemical Validation and Standardization Platform (CVSP): large-scale automated validation of chemical structure datasets

Journal of cheminformatics, 2015-06, Vol.7 (1), p.30-30, Article 30

2015

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High-performance integrated virtual environment (HIVE): a robust infrastructure for next-generation sequence data analysis

Database : the journal of biological databases and curation, 2016, Vol.2016, p.baw022

2016

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Machine Learning Models for Mycobacterium tuberculosisIn Vitro Activity: Prediction and Target Visualization

Molecular pharmaceutics, 2022-02, Vol.19 (2), p.674-689

2022

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Towards a gold standard: regarding quality in public domain chemistry databases and approaches to improving the situation

Identification of “Known Unknowns” Utilizing Accurate Mass Data and ChemSpider

Open-source QSAR models for pKa prediction using multiple machine learning approaches

Deep Learning Insights into Lanthanides Complexation Chemistry

Free and open-source QSAR-ready workflow for automated standardization of chemical structures in support of QSAR modeling

ChemTrove: Enabling a Generic ELN To Support Chemistry through the Use of Transferable Plug-ins and Online Data Sources

Graph Convolutional Neural Networks as “General-Purpose” Property Predictors: The Universality and Limits of Applicability

Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets

Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining

Size Doesn’t Matter: Predicting Physico- or Biochemical Properties Based on Dozens of Molecules

Transferable and Extensible Machine Learning-Derived Atomic Charges for Modeling Hybrid Nanoporous Materials

Machine-learning-assisted search for functional materials over extended chemical space

CATMoS: Collaborative Acute Toxicity Modeling Suite

Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery

Machine Learning Models for Mycobacterium tuberculosis In Vitro Activity: Prediction and Target Visualization

Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Datasets

ChemSpider - building a foundation for the semantic web by hosting a crowd sourced databasing platform for chemistry

The ChEMBL database as linked open data

Correction to “Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery”

Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining

Erratum: CATMoS: Collaborative Acute Toxicity Modeling Suite

Erratum: CATMoS: Collaborative Acute Toxicity Modeling Suite

The Chemical Validation and Standardization Platform (CVSP): large-scale automated validation of chemical structure datasets

High-performance integrated virtual environment (HIVE): a robust infrastructure for next-generation sequence data analysis

Machine Learning Models for Mycobacterium tuberculosisIn Vitro Activity: Prediction and Target Visualization

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