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

**Authors:** Wenchao Dan, Xinyuan Guo, Guangzhong Zhang, Hui Zhang, Jin Liu, Qiushuang Li, Yang Chen, Qingyong He

PMC · DOI: 10.1186/s13020-025-01127-9 · Chinese Medicine · 2025-06-06

## TL;DR

SinoMedminer is an R package and web app that simplifies and improves the analysis of traditional Chinese medicine data for researchers and practitioners.

## Contribution

The novel contribution is the development of an integrated R package and Shiny app for efficient and accessible TCM data mining.

## Key findings

- SinoMedminer supports data cleaning, clustering, and network analysis for TCM formulas.
- The Shiny app allows non-programmers to perform TCM data analysis interactively.
- The tool enhances big data handling and promotes digital integration in TCM research.

## 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.

## Full-text entities

- **Chemicals:** Chinese medicine (-)

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12142817/full.md

## Figures

8 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12142817/full.md

---
Source: https://tomesphere.com/paper/PMC12142817