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Formal Concept Analysis for the Identification of Combinatorial Biomarkers in Breast Cancer

机译:乳腺癌组合生物标志物鉴定的正式概念分析

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When cancer breaks out, central processes in the cell are disturbed. These disturbances are often due to abnormalities in gene expression. The microarray technology allows to monitor the expression of thousands of genes in human cells simultaneously. It is common knowledge that tumor cells show different gene expression profiles compared to normal tissue but also to tissue obtained from metastases. However, the identification of biomarkers, that is sets of genes whose expression change is highly correlated with the disease, poses a great challenge. Increasingly important is the extraction of combinatorial biomarkers. Here, the correlation to the disease is a result of the joint expression of several genes, whereas the single genes do not necessarily distinguish well between healthy and diseased tissue types. In this paper we describe how formal concept analysis can be used to identify gene combinations that are able to distinguish between tumor- and metastasis tissue in breast cancer based on microarray gene expression data.
机译:当癌症爆发时,细胞的中央过程受到干扰。这些干扰通常是由于基因表达异常所致。微阵列技术可以同时监测人类细胞中数千种基因的表达。众所周知,与正常组织相比,肿瘤细胞显示出不同的基因表达谱,而且与转移灶相比,它们显示出不同的基因表达谱。然而,鉴定生物标志物,即其表达变化与疾病高度相关的基因组,提出了巨大的挑战。组合生物标志物的提取越来越重要。在这里,与疾病的相关性是几种基因共同表达的结果,而单个基因并不一定能很好地区分健康组织和患病组织。在本文中,我们描述了基于微阵列基因表达数据的形式概念分析如何用于识别能够区分乳腺癌的肿瘤组织和转移组织的基因组合。

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