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基因发现中用于综合分析的ForeSee(4C)方法。

The ForeSee (4C) approach for integrative analysis in gene discovery.

作者信息

Guo Yike, Munro Robin E J, Kalaitzopoulos Dimitrios, Grigoriadis Anita

机构信息

Department of Computing, Imperial College London, London, UK.

出版信息

Methods Mol Biol. 2011;760:53-71. doi: 10.1007/978-1-61779-176-5_4.

Abstract

The development of high-throughput experimental techniques has made measurements for virtually all kinds of cellular components possible. Effective integration and analysis of this diverged information to produce insightful knowledge is central to biological study today. In this chapter, we present a methodology for building integrative analytical workbenches using the workflow technology. We focus on the field of gene discovery through the combined study of transcriptomics, genomics and epigenomics, although the methodology is generally applicable to any omics-data analysis for biomarker discovery. We illustrate the application of the methodology by presenting our study on the identification of aberrant genomic regions, genes and/or their regulatory elements with their implications for breast cancer research. We also discuss the challenges and opportunities brought by the latest development of the next generation sequencing technology.

摘要

高通量实验技术的发展使得对几乎所有类型的细胞成分进行测量成为可能。有效整合和分析这些分散的信息以产生有洞察力的知识是当今生物学研究的核心。在本章中,我们介绍一种使用工作流技术构建综合分析工作台的方法。我们专注于通过转录组学、基因组学和表观基因组学的联合研究进行基因发现领域,尽管该方法通常适用于任何用于生物标志物发现的组学数据分析。我们通过展示我们对异常基因组区域、基因和/或其调控元件的鉴定及其对乳腺癌研究的意义的研究,来说明该方法的应用。我们还讨论了下一代测序技术的最新发展带来的挑战和机遇。

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