Singh Surabhi, Hegde Shubhada R
Institute of Bioinformatics and Applied Biotechnology, Bengaluru, India.
School of Biosciences, Chanakya University, Bengaluru, India.
Methods Mol Biol. 2025;2927:99-113. doi: 10.1007/978-1-0716-4546-8_5.
Viruses depend on the host cells for replication and manipulate host cellular processes to assemble their components. Therefore, studying viral infections at the cellular level involves exploring interactions between viral and host proteins. These interactions can be structured as a bipartite network, where one set of nodes represents host proteins, another set represents viral proteins, and the edges symbolize the interactions between these two sets of nodes. Network theory offers a conceptual framework for identifying key proteins in the network, often referred to as centrality measures. Additionally, the projection of the bipartite network to one mode provides insights into the interactions between host proteins based on how they interact with the viral proteins. This chapter deals with the analysis of such a bipartite network of virus and host protein interactions by providing stepwise codes in the R programming language. The workflow is easily adaptable to virus-host interaction data derived from diverse experiments or databases.
病毒依赖宿主细胞进行复制,并操纵宿主细胞过程来组装其组件。因此,在细胞水平上研究病毒感染涉及探索病毒蛋白与宿主蛋白之间的相互作用。这些相互作用可以构建为一个二分网络,其中一组节点代表宿主蛋白,另一组代表病毒蛋白,边则表示这两组节点之间的相互作用。网络理论提供了一个概念框架,用于识别网络中的关键蛋白,通常称为中心性度量。此外,将二分网络投影到一种模式可以基于宿主蛋白与病毒蛋白的相互作用方式,深入了解宿主蛋白之间的相互作用。本章通过提供R编程语言的逐步代码,来处理这种病毒与宿主蛋白相互作用的二分网络分析。该工作流程很容易适用于来自不同实验或数据库的病毒-宿主相互作用数据。