Jan 16, 2018 · We developed an extendable and highly customizable fully automated QSAR modeling framework. This designed workflow does not require any advanced ...
Jan 16, 2018 · We developed an extendable and highly customizable fully automated QSAR modeling framework. This designed workflow does not require any advanced ...
Conclusions: We developed an extendable and highly customizable fully automated QSAR modeling framework. This designed workflow does not require any advanced ...
In-silico quantitative structure–activity relationship (QSAR) models based tools are widely used to screen huge databases of compounds in order to determine ...
We developed an extendable and highly customizable fully automated QSAR modeling framework. This designed workflow does not require any advanced ...
Jun 30, 2021 · In this study, we present the first KNIME automated workflow to modeling a large, diverse, and highly imbalanced dataset of compounds with antileishmanial ...
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Feb 16, 2024 · Here we present Qptuna, a molecule property prediction modelling pipeline, written in Python and utilising the Optuna, Scikit-learn, RDKit and ChemProp ...
Jul 22, 2024 · We present QSARtuna, a molecule property prediction modeling pipeline, written in Python and utilizing the Optuna, Scikit-learn, RDKit, and ChemProp packages.
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An automated framework for QSAR model building. KNIME version 3.2 (https://www.knime.org/) installation is required to import and run QSAR modeling workflow.
An automated framework for QSAR model building ; Journal: Journal of Cheminformatics, 2018, № 1 ; Publisher: Springer Science and Business Media LLC ; Authors: ...