Evidence map›Paper›PMID 41786750›Full record

ArticleScientific data2026

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

Hongying Zhao, Peiqi Ben, Zhimiao Liu, Marui Guan, Lin Lin, Dongchen Han, Jincheng Guo, Li Wang

Abstract readDataset
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Hongying Zhao *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China. zhaohongying@hrbmu.edu.cn.
Peiqi Ben *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Zhimiao Liu *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Marui GuanCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Lin LinCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China.
Dongchen HanSchool of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 100029, China.
Jincheng GuoSchool of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, 100029, China. guojincheng@bucm.edu.cn.
Li WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China. wangli@hrbmu.edu.cn.

Funding

National Natural Science Foundation of China 62372144National Natural Science Foundation of China 62572155Outstanding Youth Foundation of Heilongjiang Province of China YQ2023F004
6 · The paper itself

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.

Indexed as

Gene Expression ProfilingMedicine, Chinese TraditionalTranscriptomeHumans

Identifiers

PMID41786750
PMCPMC13083922

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.