首页> 外文会议>Pacific Symposium on Biocomputing 2001, Jan 3-7, 2001, Mauna Lani, Hawaii >MUTUAL INFORMATION ANALYSIS AS A TOOL TO ASSESS THE ROLE OF ANEUPLOIDY IN THE GENERATION OF CANCER-ASSOCIATED DIFFERENTIAL GENE EXPRESSION PATTERNS
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MUTUAL INFORMATION ANALYSIS AS A TOOL TO ASSESS THE ROLE OF ANEUPLOIDY IN THE GENERATION OF CANCER-ASSOCIATED DIFFERENTIAL GENE EXPRESSION PATTERNS

机译:互信息分析作为评估非肿瘤性在癌相关差异基因表达模式产生中的作用的工具

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摘要

Most human tumors are characterized by: (1) an aberrant set of chromosomes, a state termed aneuploidy; (2) an aberrant gene expression pattern; and (3) an aberrant phenotype of uncontrolled growth. One of the goals of cancer research is to establish causative relationships between these three important characteristics. In this paper we were searching for evidence that aneuploidy is a major cause of differential gene expression. We describe how mutual information analysis of cancer-associated gene expression patterns could be exploited to answer this question. In addition to providing general guidelines, we have applied the proposed analysis to a recently published breast cancer-associated gene expression matrix. The results derived from this particular data set provided preliminary evidence that mutual information analysis may become a useful tool to investigate the link between differential gene expression and aneuploidy.
机译:大多数人类肿瘤的特征是:(1)一组异常染色体,一种称为非整倍性的状态; (2)异常的基因表达模式; (3)生长失控的异常表型。癌症研究的目标之一是在这三个重要特征之间建立因果关系。在本文中,我们正在寻找非整倍性是差异基因表达的主要原因的证据。我们描述了如何利用癌症相关基因表达模式的相互信息分析来回答这个问题。除了提供一般准则外,我们还将拟议的分析应用于最近发表的乳腺癌相关基因表达矩阵。从该特定数据集获得的结果提供了初步的证据,即相互信息分析可能成为研究差异基因表达与非整倍性之间联系的有用工具。

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