Dataset of in vitro measured chemicals neurotoxicity
© 2024 The Authors..
To understand and describe neurotoxicity mechanistically, we must first understand the processes and responses that occur within neuronal cell systems after the administration of a chemical. The dataset we present is a collection of experimental results from the literature that comprises various neurotoxic endpoints in human-derived in vitro models, allowing for easy data analysis. Currently available and free databases such as the EPA's ToxCast, which focuses on forecasting toxic health risks, are created by collecting reports on cytotoxicity testing and creating mathematical fits that could help predict the effects of a given chemical on various types of cells. We, in contrast, provide a smaller, raw, and heterogeneous dataset created solely of results on human-derived cell models that not only summarises the cytotoxic effects of certain substances but also creates a possibility for analysing the significance of the experimental set-up for the prediction of outcome.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2024 |
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Erschienen: |
2024 |
Enthalten in: |
Zur Gesamtaufnahme - volume:54 |
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Enthalten in: |
Data in brief - 54(2024) vom: 24. Apr., Seite 110380 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Ulaszek, Seweryn [VerfasserIn] |
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Links: |
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Themen: |
3rs |
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Anmerkungen: |
Date Revised 25.04.2024 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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doi: |
10.1016/j.dib.2024.110380 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM371063434 |
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520 | |a To understand and describe neurotoxicity mechanistically, we must first understand the processes and responses that occur within neuronal cell systems after the administration of a chemical. The dataset we present is a collection of experimental results from the literature that comprises various neurotoxic endpoints in human-derived in vitro models, allowing for easy data analysis. Currently available and free databases such as the EPA's ToxCast, which focuses on forecasting toxic health risks, are created by collecting reports on cytotoxicity testing and creating mathematical fits that could help predict the effects of a given chemical on various types of cells. We, in contrast, provide a smaller, raw, and heterogeneous dataset created solely of results on human-derived cell models that not only summarises the cytotoxic effects of certain substances but also creates a possibility for analysing the significance of the experimental set-up for the prediction of outcome | ||
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650 | 4 | |a Toxicology | |
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700 | 1 | |a Polak, Sebastian |e verfasserin |4 aut | |
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