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Dataset . 2019
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2019
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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S37 | LITMINEDNEURO | Neurotoxicants from literature mining PubMed

Authors: Baker, Nancy; Schymanski, Emma; Williams, Antony;

S37 | LITMINEDNEURO | Neurotoxicants from literature mining PubMed

Abstract

A list of chemicals associated with neurotoxicity compiled through systematic literature mining of PubMed using MeSH terms, compiled by Nancy Baker, Antony Williams (US EPA) and Emma Schymanski (LCSB), details in Schymanski et al. 2019, DOI: 10.1039/C9EM00068B and on CompTox. Dataset DOI: 10.5281/zenodo.2653214 Updated 10/06/2019 to include entries that were registered but not yet publicly available when the previous version was released.

Related Organizations
Keywords

Suspect Screening, Neurotoxicants, Toxins, NeuroTox

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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90