The use of herbs to treat various human diseases has been recorded for thousands of years. In Asia's current medical system, numerous herbal formulas have been repeatedly verified to confirm their effectiveness in different periods, which is a great resource for drug innovation and discovery. Through the mining of these clinical effective formulas by network pharmacology and bioinformatics analysis, important biologically active ingredients derived from these natural products might be discovered. As modern medicine requires a combination of multiple drugs for the treatment of complex diseases, previously clinical formulas are also combinations of various herbs according to the main causes and accompanying symptoms. However, the herbs that play a major role in the treatment of diseases are always unclear. Therefore, how to rank each herb's relative importance and determine the core herbs, is the first step to assisting herb selection for active ingredients discovery. To solve this problem, we built the platform FangNet, which ranks all herbs on their relative topological importance using the PageRank algorithm, based on the constructed symptom-herb network from a collection of clinical empirical prescriptions. Three types of herb hidden knowledge, including herb importance rank, herb-herb co-occurrence, and associations to symptoms, were provided in an interactive visualization. Moreover, FangNet has designed role-based permission for teams to store, analyze, and jointly interpret their clinical formulas, in an easy and secure collaboration environment, aiming at creating a central hub for massive symptom-herb connections. FangNet can be accessed at or .

中文翻译：

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FangNet：利用结构网络算法从中医临床有效方剂中挖掘草药隐藏知识


使用草药治疗各种人类疾病已有数千年的记录。在亚洲现有的医疗体系中，无数的草药配方在不同时期都经过反复验证，证实其有效性，这是药物创新和发现的巨大资源。通过网络药理学和生物信息学分析挖掘这些临床有效的配方，可能会发现这些天然产物中重要的生物活性成分。由于现代医学需要多种药物组合来治疗复杂的疾病，以前的临床方剂也是根据主因和伴随症状，将多种药物组合在一起。然而，对于治疗疾病起主要作用的草药却始终不清楚。因此，如何对每种药材的相对重要性进行排序并确定核心药材，是辅助药材筛选、发现活性成分的第一步。为了解决这个问题，我们建立了FangNet平台，该平台基于从临床经验处方集合中构建的症状-草药网络，使用PageRank算法对所有草药按照其相对拓扑重要性进行排名。在交互式可视化中提供了三种类型的草药隐藏知识，包括草药重要性排名、草药与草药共现以及与症状的关联。此外，FangNet 还设计了基于角色的权限，让团队可以在简单、安全的协作环境中存储、分析和共同解释其临床配方，旨在为大规模症状与草药连接创建一个中心枢纽。 FangNet 可通过 或 访问。