Zheng Guangyong, Huang Tao
Bio-Med Big Data Center, Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
Methods Mol Biol. 2018;1754:137-154. doi: 10.1007/978-1-4939-7717-8_8.
In post-genomic era, an important task is to explore the function of individual biological molecules (i.e., gene, noncoding RNA, protein, metabolite) and their organization in living cells. For this end, gene regulatory networks (GRNs) are constructed to show relationship between biological molecules, in which the vertices of network denote biological molecules and the edges of network present connection between nodes (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). Biologists can understand not only the function of biological molecules but also the organization of components of living cells through interpreting the GRNs, since a gene regulatory network is a comprehensively physiological map of living cells and reflects influence of genetic and epigenetic factors (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). In this paper, we will review the inference methods of GRN reconstruction and analysis approaches of network structure. As a powerful tool for studying complex diseases and biological processes, the applications of the network method in pathway analysis and disease gene identification will be introduced.
在后基因组时代,一项重要任务是探索单个生物分子(即基因、非编码RNA、蛋白质、代谢物)的功能及其在活细胞中的组织方式。为此,构建基因调控网络(GRN)以展示生物分子之间的关系,其中网络的顶点表示生物分子,网络的边表示节点之间的连接(斯特罗加茨,《自然》410:268 - 276,2001;布雷,《科学》301:1864 - 1865,2003)。生物学家通过解读基因调控网络,不仅可以了解生物分子的功能,还能了解活细胞组成部分的组织方式,因为基因调控网络是活细胞的综合生理图谱,反映了遗传和表观遗传因素的影响(斯特罗加茨,《自然》410:268 - 276,2001;布雷,《科学》301:1864 - 1865,2003)。在本文中,我们将综述基因调控网络重建的推理方法和网络结构的分析方法。作为研究复杂疾病和生物过程的有力工具,还将介绍网络方法在通路分析和疾病基因鉴定中的应用。