An in-depth transcriptomic atlas deciphering traditional Chinese medicine mechanisms and disease associations

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Authors: Hongyun Zhao, Peiqi Ben, Zhimiao Liu, Marui Guan, Lin L. Lin, Dongchen Han, Jincheng Guo, Le Wang
Cited by: 0
References: 13

Abstract

Transcriptomic profiling of Traditional Chinese Medicine (TCM) perturbations is essential for elucidating the molecular mechanisms of therapeutic interventions. Although data from TCM treatment experiments are scattered across public repositories, a comprehensive, harmonized dataset remains unavailable due to heterogeneous experimental designs and inconsistent metadata. Here, we present a curated, harmonized resource comprising 362 human gene expression profiles derived from 27 TCMs and 137 TCM-derived ingredients spanning 26 human disease contexts, re-processed via a unified bioinformatics pipeline. This atlas captures TCM-induced genome-wide alterations in both protein-coding genes and long non-coding RNAs. We confirmed the dataset's biological fidelity by validating the high reproducibility of the dataset, the enrichment of known pharmacological targets, and recapitulated the well-established therapeutic associations between TCM and disease treatment. This standardized dataset serves as a foundational resource for researchers to systematically investigate therapeutic mechanisms and predict clinical indications of TCM.

Fields of Study & Subjects

Traditional Chinese Medicine Studies Traditional Chinese Medicine Analysis Computational Drug Discovery Methods

Publication details

Journal / source
Scientific Data
Volume
13
Issue
1
Publication date
5 March 2026
Language
EN