目的 应用基于超图的超网络理论，构建中药方剂超网络并探究其群体的拓扑特性，以期挖掘药材的群组信息及其高阶关联关系。方法 收集整理书籍《实用三味中医药方》和中医药信息数据库（TCM-ID）中的中药方剂，分别得到2个中药方剂数据库。以每首中药方剂作为超边，相应方剂中出现的每味药材作为节点，构建中药方剂超网络模型。通过计算中药方剂超网络的拓扑指标，重点对组度序列及组度分布规律进行分析，并借助Python软件中的Pyplot功能呈现可视化结果。结果 2个数据集共收录9 234首方剂，根据2个数据集的不同来源分别构建均匀超网络模型和非均匀超网络模型。其中，均匀超网络模型中共有2 719首方剂，涉及1 404味药材，频数最大的二元药材群组是{黄连，黄芩}，黄芩虽然是二元药材群组中的重要组成药材，但却未出现在排名前10的单味药材中；非均匀超网络模型中共有6 515首方剂，涉及2 381味药材，频数最大的三元药材群组是{黄连，黄芩，甘草}，黄连虽然是排名第1的三元药材群组中的重要组成药材，但其单味药材排名却是第7。2个中药方剂超网络的各类组度分布服从幂律分布，表明药材群组的分布具有无标度特性，提示频数越大的药材群组越重要。结论 中药方剂中的药材从药理上具有互补性，仅评估单味药材或药对重要性的视角较单一，使用基于超图的超网络对中药方剂系统进行建模，突破了使用普通复杂网络建模中基于点对关联的局限，可更好地描述中药方剂这一现实复杂系统中的高阶交互关系，从而能够有效地挖掘出中药方剂中重要的药材群组，且组度值大的药材群组中药材之间具有紧密的多重关联性可为新方研发和创新用药等提供理论参考。

Objective The hypernetwork theory based on hypergraph is applied to construct the hypernetwork of traditional Chinese medicine prescriptions, explore the topological characteristics of its group, and mine the group information and high-order association relationship of medicinal materials. Methods Sorting out the prescriptions in the book “Practical Three-flavor Traditional Chinese Medicine Prescriptions” and traditional Chinese medicine information databas (TCM-ID), and obtaining two traditional Chinese medicine prescription databases, respectively. Each traditional Chinese medicine prescription as super edge, every medicinal material as the node to build a hypernetwork model of traditional Chinese medicine prescriptions. By calculating the topological index of the hypernetwork, the composition sequence and distribution law are analyzed, and the visual results are presented with the help of Pyplot function in Python software. Results A total of 9 234 prescriptions are included in the two datasets, and uniform and non-uniform hypernetworks models were constructed depending on the different sources of the two datasets. In the uniform hypernetwork model, there were 2 719 prescriptions and 1 404 herbs, and Huanglian (Coptidis Rhizoma) and Huangqin (Scutellariae Radix) were the largest frequent herbs in the two-tuple group. Although Scutellariae Radix was an important herb in the two-tuple group, it did not appear in the top 10 single herbs. In the non-uniform hypernetwork model, there were 6 515 prescriptions and 2 381 herbs. The three tuple herbal groups with the largest frequency were Coptidis Rhizoma, Scutellariae Radix and Gancao (Glycyrrhizae Radix et Rhizoma). Although Coptidis Rhizoma was important herb in the three-tuple herbal group ranked first, its single herbal medicine ranking was the seventh. The group degree distribution of the two traditional Chinese medicine prescription hypernetwork obeys the power-law distribution, indicating that the distribution of drug group has the scale-free property, which mean that the drug group with greater frequency was more important. Conclusion The medicinal herbs in the prescription system are pharmacologically complementary, the perspective of evaluating the importance of single medicinal materials or herb pairs is relatively simple, the use of hypergraph-based hypernetwork modeling of traditional Chinese medicine prescription system breaks through the limitation of point-pair association in ordinary complex network modeling. It is conducive to better describe the high-order interactions in the real-world complex system of prescriptions and effectively excavate the important medicinal material groups in the prescriptions. In addition, there are close multiple correlations among the medicinal materials in the medicinal materials groups with large grouping value, which can provide theoretical reference for the research and development of new prescriptions and innovative drugs.

G350；R283.21

国家自然科学基金区域创新发展联合基金（U20A20228）；湖州市科技计划自然科学资金项目（2022YZ53）；湖州师范学院研究生科研创新项目课题（2024KYCX74）