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Discovery of dominant and dormant genes from expression data using a novel generalization of SNR for multi-class problems

机译:使用SNR的新颖概括性从表达数据中发现优势基因和休眠基因以解决多类问题

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摘要

BackgroundThe Signal-to-Noise-Ratio (SNR) is often used for identification of biomarkers for two-class problems and no formal and useful generalization of SNR is available for multiclass problems. We propose innovative generalizations of SNR for multiclass cancer discrimination through introduction of two indices, Gene Dominant Index and Gene Dormant Index (GDIs). These two indices lead to the concepts of dominant and dormant genes with biological significance. We use these indices to develop methodologies for discovery of dominant and dormant biomarkers with interesting biological significance. The dominancy and dormancy of the identified biomarkers and their excellent discriminating power are also demonstrated pictorially using the scatterplot of individual gene and 2-D Sammon's projection of the selected set of genes. Using information from the literature we have shown that the GDI based method can identify dominant and dormant genes that play significant roles in cancer biology. These biomarkers are also used to design diagnostic prediction systems.
机译:背景技术信噪比(SNR)通常用于识别两类问题的生物标志物,并且没有针对多类问题的SNR形式化和有用的概括。我们通过引入基因优势指数和基因休眠指数(GDI)两个指数,提出了针对多类癌症鉴别的SNR的创新概括。这两个指数导致了具有生物学意义的显性基因和休眠基因的概念。我们使用这些指数来开发发现具有有趣生物学意义的显性和休眠生物标志物的方法。还使用单个基因的散点图和所选基因组的二维Sammon投影,以图形方式展示了已识别生物标志物的优势和休眠及其出色的区分能力。使用来自文献的信息,我们表明基于GDI的方法可以识别在癌症生物学中起重要作用的显性和休眠基因。这些生物标志物还用于设计诊断预测系统。

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