首页> 外文期刊>Mutation Research: International Journal on Mutagenesis, Chromosome Breakage and Related Subjects >A data mining approach for the elucidation of the action of putative etiological agents: application to the non-genotoxic carcinogenicity of genistein.
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A data mining approach for the elucidation of the action of putative etiological agents: application to the non-genotoxic carcinogenicity of genistein.

机译:阐明推测病因的作用的数据挖掘方法:在染料木黄酮的非遗传毒性致癌性中的应用。

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摘要

A procedure designated "the virtual similarity index" (VSI) is described to determine the probability that two or more toxicants are related mechanistically. The approach is structure-activity relationship (SAR) based and generates the virtual toxicological profiles of the chemicals under investigation. It also determines the similarities between them. That commonality is compared to the frequency with which it is found among a population of 10,000 chemicals representing the "universe of chemicals". The similarities between the candidate chemicals and chemicals known to act by other recognized mechanisms are also determined. If the similarities between the candidate chemicals are significantly greater than for the non-related ones, the chemicals are assumed to act by a common mechanism. In that context, the putative non-genotoxic mechanism responsible for the carcinogenicity of genistein (GEN) and its relationship to the action of diethylstilbestrol is examined.
机译:描述了一种称为“虚拟相似性指数”(VSI)的过程,以确定两种或多种有毒物质在机械上相关的可能性。该方法基于结构-活性关系(SAR),并生成了所研究化学品的虚拟毒理学概况。它还确定了它们之间的相似性。将这种共性与代表“化学物质宇宙”的10,000种化学物质中被发现的频率进行比较。还确定了候选化学物质与已知通过其他公认机制起作用的化学物质之间的相似性。如果候选化学物质之间的相似性远大于非相关化学物质之间的相似性,则假定这些化学物质具有共同的机制。在这种情况下,检查了可能的染料木黄酮(GEN)致癌性及其与己烯雌酚作用的关系的非遗传毒性机理。

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