Li Rong, Yi Huangdi, Ma Shuangge
Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Servier Pharmaceuticals, Boston, MA, USA.
Methods Mol Biol. 2025;2880:293-307. doi: 10.1007/978-1-0716-4276-4_14.
With the development of high-throughput profiling techniques, gene expressions have drawn significant attention due to their important biological implications, widespread data availability, and promising biological findings. The complex interactions and regulations among genes naturally lead to a network structure, which can provide a global view of molecular mechanisms and biological processes. This chapter provides a selective overview of constructing gene expression networks and utilizing them in downstream analysis. It also includes a demonstrating example.
随着高通量分析技术的发展,基因表达因其重要的生物学意义、广泛的数据可用性以及有前景的生物学发现而备受关注。基因之间复杂的相互作用和调控自然地导致了一种网络结构,这种结构能够提供分子机制和生物学过程的全局视图。本章对构建基因表达网络及其在下游分析中的应用进行了选择性概述。还包括一个示例演示。