Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS, 66506, USA.
Division of Biology, Kansas State University, Manhattan, KS, 66506, USA.
BMC Bioinformatics. 2023 Jul 11;24(1):281. doi: 10.1186/s12859-023-05382-1.
Network analysis is a powerful tool for studying gene regulation and identifying biological processes associated with gene function. However, constructing gene co-expression networks can be a challenging task, particularly when dealing with a large number of missing values.
We introduce GeCoNet-Tool, an integrated gene co-expression network construction and analysis tool. The tool comprises two main parts: network construction and network analysis. In the network construction part, GeCoNet-Tool offers users various options for processing gene co-expression data derived from diverse technologies. The output of the tool is an edge list with the option of weights associated with each link. In network analysis part, the user can produce a table that includes several network properties such as communities, cores, and centrality measures. With GeCoNet-Tool, users can explore and gain insights into the complex interactions between genes.
网络分析是研究基因调控和识别与基因功能相关的生物过程的有力工具。然而,构建基因共表达网络可能是一项具有挑战性的任务,特别是在处理大量缺失值时。
我们引入了 GeCoNet-Tool,这是一种集成的基因共表达网络构建和分析工具。该工具包括两个主要部分:网络构建和网络分析。在网络构建部分,GeCoNet-Tool 为用户提供了多种选项来处理来自不同技术的基因共表达数据。该工具的输出是一个带有与每个链接相关的权重的边列表。在网络分析部分,用户可以生成一个包含多个网络属性(如社区、核心和中心性度量)的表格。使用 GeCoNet-Tool,用户可以探索和深入了解基因之间的复杂相互作用。