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Discovery of Biomarkers for Hexachlorobenzene Toxicity Using Population Based Methods on Gene Expression Data

机译:基于基因表达数据的人群方法发现六氯苯毒性生物标志物

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Discovering toxicity biomarkers is important in drug discovery to safely evaluate possible toxic effects of a substance in early phases. We tried evolutionary classification methods for selecting the important classifier genes in hexachlorobenzene toxicity using microarray data. Using modified genetic algorithms for selection of minimum number of features for classification of gene expression data, we discovered a number of gene sets of size 4 that were able to discriminate between the control and the hexachlorobenzene (HCB) exposed group of Brown-Norway rats with >99% accuracy in 5-fold cross-validation tests, whereas classification using all of the genes with SVM and other methods yielded results that vary between 48.48% to 81.81%. Making use of this small number of genes as biomarkers may allow us to detect toxicity of substances with mechanisms of toxicity similar to HCB in a fast and cost efficient manner when there are no emerging symptoms.
机译:发现毒性生物标志物对于药物开发非常重要,可以安全地评估物质在早期阶段可能产生的毒性作用。我们尝试了进化分类方法,以利用微阵列数据选择六氯苯毒性中的重要分类基因。使用改良的遗传算法选择最少数量的特征进行基因表达数据分类,我们发现了许多大小为4的基因集,它们能够区分对照组和六氯苯(HCB)暴露组的布朗-挪威大鼠,在5倍交叉验证测试中,准确率> 99%,而使用SVM和其他方法对所有基因进行分类产生的结果在48.48%至81.81%之间变化。利用这种少量基因作为生物标记,可以使我们在没有新出现症状的情况下,以快速且经济高效的方式检测具有类似于HCB毒性机制的物质的毒性。

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