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Dataset on aquatic ecotoxicity predictions of 2697 chemicals, using three quantitative structure-activity relationship platforms

Empirical and in silico data on the aquatic ecotoxicology of 2697 organic chemicals were collected in order to compile a dataset for assessing the predictive power of current Quantitative Structure Activity Relationship (QSAR) models and software platforms. This document presents the dataset and the...

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Autores principales: Svedberg, Patrik, Inostroza, Pedro A., Gustavsson, Mikael, Kristiansson, Erik, Spilsbury, Francis, Backhaus, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10641136/
https://www.ncbi.nlm.nih.gov/pubmed/37965605
http://dx.doi.org/10.1016/j.dib.2023.109719
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author Svedberg, Patrik
Inostroza, Pedro A.
Gustavsson, Mikael
Kristiansson, Erik
Spilsbury, Francis
Backhaus, Thomas
author_facet Svedberg, Patrik
Inostroza, Pedro A.
Gustavsson, Mikael
Kristiansson, Erik
Spilsbury, Francis
Backhaus, Thomas
author_sort Svedberg, Patrik
collection PubMed
description Empirical and in silico data on the aquatic ecotoxicology of 2697 organic chemicals were collected in order to compile a dataset for assessing the predictive power of current Quantitative Structure Activity Relationship (QSAR) models and software platforms. This document presents the dataset and the data pipeline for its creation. Empirical data were collected from the US EPA ECOTOX Knowledgebase (ECOTOX) and the EFSA (European Food Safety Authority) report “Completion of data entry of pesticide ecotoxicology Tier 1 study endpoints in a XML schema – database”. Only data for OECD recommended algae, daphnia and fish species were retained. QSAR toxicity predictions were calculated for each chemical and each of six endpoints using ECOSAR, VEGA and the Toxicity Estimation Software Tool (T.E.S.T.) platforms. Finally, the dataset was amended with SMILES, InChIKey, pKa and logP collected from webchem and PubChem.
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spelling pubmed-106411362023-11-14 Dataset on aquatic ecotoxicity predictions of 2697 chemicals, using three quantitative structure-activity relationship platforms Svedberg, Patrik Inostroza, Pedro A. Gustavsson, Mikael Kristiansson, Erik Spilsbury, Francis Backhaus, Thomas Data Brief Data Article Empirical and in silico data on the aquatic ecotoxicology of 2697 organic chemicals were collected in order to compile a dataset for assessing the predictive power of current Quantitative Structure Activity Relationship (QSAR) models and software platforms. This document presents the dataset and the data pipeline for its creation. Empirical data were collected from the US EPA ECOTOX Knowledgebase (ECOTOX) and the EFSA (European Food Safety Authority) report “Completion of data entry of pesticide ecotoxicology Tier 1 study endpoints in a XML schema – database”. Only data for OECD recommended algae, daphnia and fish species were retained. QSAR toxicity predictions were calculated for each chemical and each of six endpoints using ECOSAR, VEGA and the Toxicity Estimation Software Tool (T.E.S.T.) platforms. Finally, the dataset was amended with SMILES, InChIKey, pKa and logP collected from webchem and PubChem. Elsevier 2023-10-24 /pmc/articles/PMC10641136/ /pubmed/37965605 http://dx.doi.org/10.1016/j.dib.2023.109719 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Svedberg, Patrik
Inostroza, Pedro A.
Gustavsson, Mikael
Kristiansson, Erik
Spilsbury, Francis
Backhaus, Thomas
Dataset on aquatic ecotoxicity predictions of 2697 chemicals, using three quantitative structure-activity relationship platforms
title Dataset on aquatic ecotoxicity predictions of 2697 chemicals, using three quantitative structure-activity relationship platforms
title_full Dataset on aquatic ecotoxicity predictions of 2697 chemicals, using three quantitative structure-activity relationship platforms
title_fullStr Dataset on aquatic ecotoxicity predictions of 2697 chemicals, using three quantitative structure-activity relationship platforms
title_full_unstemmed Dataset on aquatic ecotoxicity predictions of 2697 chemicals, using three quantitative structure-activity relationship platforms
title_short Dataset on aquatic ecotoxicity predictions of 2697 chemicals, using three quantitative structure-activity relationship platforms
title_sort dataset on aquatic ecotoxicity predictions of 2697 chemicals, using three quantitative structure-activity relationship platforms
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10641136/
https://www.ncbi.nlm.nih.gov/pubmed/37965605
http://dx.doi.org/10.1016/j.dib.2023.109719
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