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

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    Type
    Article
    Authors
    Raies, Arwa B. cc
    Bajic, Vladimir B. cc
    KAUST Department
    Computational Bioscience Research Center (CBRC)
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Applied Mathematics and Computational Science Program
    Date
    2016-01-06
    Online Publication Date
    2016-01-06
    Print Publication Date
    2016-03
    Permanent link to this record
    http://hdl.handle.net/10754/593340
    
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    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.
    Citation
    In silico toxicology: computational methods for the prediction of chemical toxicity 2016:n/a Wiley Interdisciplinary Reviews: Computational Molecular Science
    Publisher
    Wiley
    Journal
    Wiley Interdisciplinary Reviews: Computational Molecular Science
    DOI
    10.1002/wcms.1240
    10.1002/wcms.1254
    PubMed ID
    27066112
    Additional Links
    http://doi.wiley.com/10.1002/wcms.1240
    ae974a485f413a2113503eed53cd6c53
    10.1002/wcms.1240
    Scopus Count
    Collections
    Articles; Applied Mathematics and Computational Science Program; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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