微阵列数据集的数据挖掘技术

Lei Liu, Jiong Yang, A. Tung
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引用次数: 6

摘要

数据挖掘研究侧重于从数据库中可扩展和有效地发现知识,可以为生物学家在这些方面提供及时的解决方案。在本文中,我们的目标是提供一个平台,在这个平台上介绍了微阵列数据分析的各个方面。我们在外行术语中讨论如何生成微阵列数据集并在生物学研究中使用。我们用我们参与的实际项目中的例子来说明不同技术的潜力。我们还讨论了用于分析微阵列数据集及其生物学意义的现有数据挖掘工具和方法。我们还提供广泛的分析工具,可应用于微阵列基因表达分析。最后,我们提出了微阵列数据分析有待解决的问题和未来的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data mining techniques for microarray datasets
Data mining research, which focuses on scalable and effective knowledge discovery from databases, can provide timely solutions for the biologists in these aspects. In this article, we aim to provide platform in which various aspects of microarray data analysis is being introduced. We discuss in layman term how microarray datasets are generated and used in biological research. We use example from the real projects that we participate in to illustrate the potential of different technologies. We also discuss existing data mining tools and methods used for analyzing the microarray data sets and their biological implications. We also offer a wide range of analysis tools that can be applied to microarray gene expression analysis. Finally, we present a set of open problems and future research directions for microarray data analysis.
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