Data Mining and in Silico Analysis of Ethiopian Traditional Medicine: Unveiling the Therapeutic Potential of Rumex abyssinicus Jacq
Lemessa Etana Bultum, Gwangmin Kim, Seon-Woo Lee, Doheon Lee

TL;DR
This study analyzes Ethiopian traditional medicine data to identify effective treatments, highlighting Rumex abyssinicus Jacq.'s potential for wound healing and other diseases.
Contribution
The study introduces a data-driven approach to validate traditional Ethiopian medicine using association rule mining and in silico analysis.
Findings
Rumex abyssinicus Jacq. is strongly associated with wound healing in traditional prescriptions.
In silico analysis revealed 756 therapeutic targets linked to multiple diseases via KEGG pathways.
Hub genes from the PPI network support the traditional use of R. abyssinicus Jacq. for wound healing.
Abstract
Multicomponent traditional medicine prescriptions are widely used in Ethiopia for disease treatment. However, inconsistencies across practitioners, cultures, and locations have hindered the development of reliable therapeutic medicines. Systematic analysis of traditional medicine data is crucial for identifying consistent and reliable medicinal materials. In this study, we compiled and analyzed a dataset of 505 prescriptions, encompassing 567 medicinal materials used for treating 106 diseases. Using association rule mining, we identified significant associations between diseases and medicinal materials. Notably, wound healing—the most frequently treated condition—was strongly associated with Rumex abyssinicus Jacq., showing a high support value. This association led to further in silico and network analysis of R. abyssinicus Jacq. compounds, revealing 756 therapeutic targets enriched in…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
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Taxonomy
TopicsEthnobotanical and Medicinal Plants Studies · Computational Drug Discovery Methods · Ginger and Zingiberaceae research
