Manually finding relationship networks among compounds can be a hard and time-consuming task. However, this process is fundamental when looking for a metabolic pathway that explains how multiple compounds are related, to identify relevant pathways in organisms, filling gaps on metabolic networks, or when new mechanisms for the synthesis of important compounds are sought.

Here, we present PhDSeeker, a new tool for the automatic search of metabolic pathways. This tool is able to relate simultaneously several compounds. Furthermore, its flexibility allows it to be easily configured for addressing a wide range of situations. Solutions found are provided not only in plain text but also as interactive representations that can be analyzed in a web browser.

Source code is available at https://github.com/sinc-lab/phdseeker. A web service is also available at https://sinc.unl.edu.ar/web-demo/phds/. Several fully documented study cases, including their settings and solutions files, are also provided as Supplementary Material.

手动查找化合物之间的关系网络可能是一项艰巨且耗时的任务。然而，在寻找解释多种化合物如何相关的代谢途径、确定生物体中的相关途径、填补代谢网络上的空白或寻找合成重要化合物的新机制时，这一过程至关重要。

在这里，我们展示了 PhDSeeker，这是一种用于自动搜索代谢途径的新工具。该工具能够同时关联多个化合物。此外，它的灵活性使其可以轻松配置以解决各种情况。找到的解决方案不仅以纯文本形式提供，而且以可在 Web 浏览器中进行分析的交互式表示形式提供。

源代码可在 https://github.com/sinc-lab/phdseeker 获得。也可在 https://sinc.unl.edu.ar/web-demo/phds/ 获得网络服务。几个完整记录的研究案例，包括它们的设置和解决方案文件，也作为补充材料提供。