生物信息学
计算生物学
计算机科学
数据科学
毒理
生化工程
生物
工程类
遗传学
基因
出处
期刊:Mutagenesis
[Oxford University Press]
日期:2018-07-14
卷期号:34 (1): 1-2
被引量:5
标识
DOI:10.1093/mutage/gey018
摘要
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.
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