SinoMedminer: an R package and shiny application for mining and visualizing traditional Chinese medicine herbal formulas

This study addresses limitations of mainstream approaches in traditional Chinese medicine (TCM) data mining by developing the SinoMedminer R package and its Shiny web application. The R package's core functionalities include data cleaning, transformation, TCM attribute statistics, association rule exploration and analysis, clustering analysis, co-occurrence network analysis, formula similarity analysis, formula identification, and dosage analysis. This package enables efficient project analyses without requiring complex coding. The accompanying Shiny web application provides an interactive, menu-driven interface for users without programming knowledge. SinoMedminer combines the computational power of a programming language with user-friendly accessibility, significantly enhancing the efficiency and standardization of TCM data mining research. A deployed server platform further simplifies access and usability by allowing direct utilization of the Shiny application. By optimizing data processing and analysis workflows, SinoMedminer enhances big data handling capabilities, accelerates research progress and product development, and promotes the integration of digital technologies into TCM research and clinical practice.

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Publication Details

Journal
Chinese Medicine
Published
2025-06-06
DOI
https://doi.org/10.1186/s13020-025-01127-9
Primary Topic
Traditional Chinese Medicine Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

SinoMedminer: an R package and shiny application for mining and visualizing traditional Chinese medicine herbal formulas

Wenchao Dan, Qingyong He, Xinyu Guo, Hui Zhang et al.
Chinese Medicine
Traditional Chinese Medicine Studies
article

SinoMedminer: an R package and shiny application for mining and visualizing traditional Chinese medicine herbal formulas

Wenchao Dan, Qingyong He, Xinyu Guo, Hui Zhang, Chen Yang, Jin Liu, Guangzhong Zhang, Qiushuang Li
article en

Abstract

This study addresses limitations of mainstream approaches in traditional Chinese medicine (TCM) data mining by developing the SinoMedminer R package and its Shiny web application. The R package's core functionalities include data cleaning, transformation, TCM attribute statistics, association rule exploration and analysis, clustering analysis, co-occurrence network analysis, formula similarity analysis, formula identification, and dosage analysis. This package enables efficient project analyses without requiring complex coding. The accompanying Shiny web application provides an interactive, menu-driven interface for users without programming knowledge. SinoMedminer combines the computational power of a programming language with user-friendly accessibility, significantly enhancing the efficiency and standardization of TCM data mining research. A deployed server platform further simplifies access and usability by allowing direct utilization of the Shiny application. By optimizing data processing and analysis workflows, SinoMedminer enhances big data handling capabilities, accelerates research progress and product development, and promotes the integration of digital technologies into TCM research and clinical practice.

Chinese MedicineVol. 20(1)
Zhejiang Chinese Medical University (CN), Capital Medical University (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Guang’anmen Hospital (CN), Beijing Hospital of Traditional Chinese Medicine (CN), Shaanxi University of Chinese Medicine (CN)
China Academy of Chinese Medical Sciences
Industry, innovation and infrastructure
Openalex Percentile: Top 80%
Traditional Chinese Medicine Studies
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