Literature DB >> 30059987

In silico approaches to genetic toxicology: progress and future.

Romualdo Benigni1.   

Abstract

Computational toxicology, also called 'in silico toxicology', is based on scientific knowledge gained from different scientific fields and on the premise that the toxicity of a chemical, depending on its intrinsic nature, can be predicted from its molecular structure and inferred from the properties of similar compounds whose activities are known. With the aim of providing faster, more economical, animal-free tools for predicting toxicity, the 'old' and well established science of Structure-Activity Relationships plays a crucial role, with increasing applications to the assessment of chemical genotoxicity and carcinogenicity. The development of the Structure-Activity Relationships algorithms is a continuous process, and new models, as well as newer versions of applications, are continuously becoming available. This Mutagenesis Special Issue presents a collection of papers on the recent advances in the field, and provides a precious snapshot in time with the most updated information available today.
© The Author(s) 2018. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Mesh:

Substances:

Year:  2019        PMID: 30059987     DOI: 10.1093/mutage/gey018

Source DB:  PubMed          Journal:  Mutagenesis        ISSN: 0267-8357            Impact factor:   3.000


  1 in total

Review 1.  In silico prediction of toxicity and its applications for chemicals at work.

Authors:  Kyung-Taek Rim
Journal:  Toxicol Environ Health Sci       Date:  2020-05-14
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.