Graphery：生物网络算法的交互式教程
Graphery: Interactive Tutorials for Biological Network Algorithms
AI总结：
Graphery 是一个面向生物学研究人员的交互式教程网络服务器，通过可执行 Python 代码和真实生物网络可视化，帮助用户理解图统计与经典图算法概念，并支持无账户代码修改，致力于发展为社区贡献的学习平台。
摘要：
网络提供了一种有意义的表示和分析复杂生物信息的方式，但基于网络的工具的方法学细节通常是为技术受众描述的。Graphery 是一个实践教程网络服务器，旨在帮助生物学研究人员理解常用图算法背后的基本概念。每个教程都描述了一个图概念以及可执行的 Python 代码，该代码在代码视图和图视图中可视化该概念。Graphery 教程帮助研究人员理解图统计（如度分布和网络模块性）和经典图算法（如最短路径和随机游走）。用户可以使用他们选择的真实世界生物网络来浏览每个教程，规模从分子相互作用图到生态网络不等。Graphery 还允许用户修改每个教程中的代码或编写新程序，所有这些都可以在无需账户的情况下执行。专注于学科的教程对于帮助研究人员解释其生物数据至关重要。Graphery 接受新教程和数据集的想法，这些想法将由计算和生物学研究人员共同塑造，发展成为一个社区贡献的学习平台。可用性：Graphery 可在 https://graphery.reedcompbio.org/ 获取。
英文摘要：
Networks provide a meaningful way to represent and analyze complex biological information, but the methodological details of network-based tools are often described for a technical audience. Graphery is a hands-on tutorial webserver designed to help biological researchers understand the fundamental concepts behind commonly-used graph algorithms. Each tutorial describes a graph concept along with executable Python code that visualizes the concept in a code view and a graph view. Graphery tutorials help researchers understand graph statistics (such as degree distribution and network modularity) and classic graph algorithms (such as shortest paths and random walks). Users navigate each tutorial using their choice of real-world biological networks, ranging in scale from molecular interaction graphs to ecological networks. Graphery also allows users to modify the code within each tutorial or write new programs, which all can be executed without requiring an account. Discipline-focused tutorials will be essential to help researchers interpret their biological data. Graphery accepts ideas for new tutorials and datasets that will be shaped by both computational and biological researchers, growing into a community-contributed learning platform. Availability: Graphery is available at https://graphery.reedcompbio.org/.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
