The importance of mathematical modelling in chemical risk assessment and the associated quantification of uncertainty

Gosling, JP orcid.org/0000-0002-4072-3022 (2019) The importance of mathematical modelling in chemical risk assessment and the associated quantification of uncertainty. Computational Toxicology, 10. pp. 44-50. ISSN 2468-1113

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2018, Elsevier B.V. This is an author produced version of an article published in Computational Toxicology. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: In silico predictions; Mathematical modelling; Next generation risk assessment; Uncertainty
Dates:
  • Published: May 2019
  • Accepted: 16 December 2018
  • Published (online): 22 December 2018
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Maths and Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds)
Funding Information:
FunderGrant number
NC3RsNC/K001280/1
Depositing User: Symplectic Publications
Date Deposited: 18 Dec 2018 12:35
Last Modified: 22 Dec 2019 01:39
Status: Published
Publisher: Elsevier
Identification Number: https://doi.org/10.1016/j.comtox.2018.12.004

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