In silico toxicology: computational methods for the prediction of chemical toxicity

Handle URI:
http://hdl.handle.net/10754/593340
Title:
In silico toxicology: computational methods for the prediction of chemical toxicity
Authors:
Raies, Arwa B.; Bajic, Vladimir B. ( 0000-0001-5435-4750 )
Abstract:
Determining the toxicity of chemicals is necessary to identify their harmful effects on humans, animals, plants, or the environment. It is also one of the main steps in drug design. Animal models have been used for a long time for toxicity testing. However, in vivo animal tests are constrained by time, ethical considerations, and financial burden. Therefore, computational methods for estimating the toxicity of chemicals are considered useful. In silico toxicology is one type of toxicity assessment that uses computational methods to analyze, simulate, visualize, or predict the toxicity of chemicals. In silico toxicology aims to complement existing toxicity tests to predict toxicity, prioritize chemicals, guide toxicity tests, and minimize late-stage failures in drugs design. There are various methods for generating models to predict toxicity endpoints. We provide a comprehensive overview, explain, and compare the strengths and weaknesses of the existing modeling methods and algorithms for toxicity prediction with a particular (but not exclusive) emphasis on computational tools that can implement these methods and refer to expert systems that deploy the prediction models. Finally, we briefly review a number of new research directions in in silico toxicology and provide recommendations for designing in silico models.
KAUST Department:
Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
In silico toxicology: computational methods for the prediction of chemical toxicity 2016:n/a Wiley Interdisciplinary Reviews: Computational Molecular Science
Publisher:
Wiley-Blackwell
Journal:
Wiley Interdisciplinary Reviews: Computational Molecular Science
Issue Date:
6-Jan-2016
DOI:
10.1002/wcms.1240
Type:
Article
ISSN:
17590876
Additional Links:
http://doi.wiley.com/10.1002/wcms.1240
Appears in Collections:
Articles; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorRaies, Arwa B.en
dc.contributor.authorBajic, Vladimir B.en
dc.date.accessioned2016-01-13T09:38:55Zen
dc.date.available2016-01-13T09:38:55Zen
dc.date.issued2016-01-06en
dc.identifier.citationIn silico toxicology: computational methods for the prediction of chemical toxicity 2016:n/a Wiley Interdisciplinary Reviews: Computational Molecular Scienceen
dc.identifier.issn17590876en
dc.identifier.doi10.1002/wcms.1240en
dc.identifier.urihttp://hdl.handle.net/10754/593340en
dc.description.abstractDetermining the toxicity of chemicals is necessary to identify their harmful effects on humans, animals, plants, or the environment. It is also one of the main steps in drug design. Animal models have been used for a long time for toxicity testing. However, in vivo animal tests are constrained by time, ethical considerations, and financial burden. Therefore, computational methods for estimating the toxicity of chemicals are considered useful. In silico toxicology is one type of toxicity assessment that uses computational methods to analyze, simulate, visualize, or predict the toxicity of chemicals. In silico toxicology aims to complement existing toxicity tests to predict toxicity, prioritize chemicals, guide toxicity tests, and minimize late-stage failures in drugs design. There are various methods for generating models to predict toxicity endpoints. We provide a comprehensive overview, explain, and compare the strengths and weaknesses of the existing modeling methods and algorithms for toxicity prediction with a particular (but not exclusive) emphasis on computational tools that can implement these methods and refer to expert systems that deploy the prediction models. Finally, we briefly review a number of new research directions in in silico toxicology and provide recommendations for designing in silico models.en
dc.language.isoenen
dc.publisherWiley-Blackwellen
dc.relation.urlhttp://doi.wiley.com/10.1002/wcms.1240en
dc.rightsThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.http://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.titleIn silico toxicology: computational methods for the prediction of chemical toxicityen
dc.typeArticleen
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalWiley Interdisciplinary Reviews: Computational Molecular Scienceen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorRaies, Arwa B.en
kaust.authorBajic, Vladimir B.en
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