Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA.
Cancer Lett. 2013 Nov 1;340(2):277-83. doi: 10.1016/j.canlet.2012.11.033. Epub 2012 Nov 29.
Current limitation in cancer genomic studies is a lack of the integration of various omics data generated through next generation sequencing technologies, as well as a lack of the sounding and comprehensive epigenomic and genomic information about a particular cancer cell type. In this review, we will discuss main aspects of current genomics research with its application in cancer topics. We will first overview the next-generation sequencing technologies, then outline the major computational approaches, particularly focusing on ChIP-based omics data, and list several remaining open questions facing computational biologists, further present regulatory network analysis inferred from the ChIP-based omics data; finally implicate the clinical outcomes from the network and pathway analysis.
当前癌症基因组研究的局限性在于缺乏通过下一代测序技术生成的各种组学数据的整合，也缺乏对特定癌细胞类型的全面而深入的表观基因组学和基因组信息。在这篇综述中，我们将讨论当前基因组学研究的主要方面及其在癌症研究中的应用。我们将首先概述下一代测序技术，然后概述主要的计算方法，特别是重点介绍基于 ChIP 的组学数据，并列出计算生物学家面临的几个悬而未决的问题，进一步从基于 ChIP 的组学数据中推断出调控网络分析；最后从网络和途径分析中暗示临床结果。
