Evidence map›Paper›PMID 35610020›Full record

ReviewJournal of traditional Chinese medicine = Chung i tsa chih ying wen pan2022

Integration strategy of network pharmacology in Traditional Chinese Medicine: a narrative review.

W U Jiashuo, Zhang Fangqing, L I Zhuangzhuang, Jin Weiyi, Shi Yue

Abstract readReview
In one paragraph

Review in Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 128 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
128citing papers in PubMed, 1 pooled it
–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

128 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  12. Antitumor Study of the Miao MedicineCurrent issues in molecular biology · 2026
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68 more citing papers are in PubMed but not listed here.

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

5 authors.

W U JiashuoInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China.
Zhang FangqingInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China.
L I ZhuangzhuangInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China.
Jin WeiyiHebei Medical University, Shijiazhuang 050017, China.
Shi YueInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional Chinese Medicine (TCM) has been extensively used as a mainstay for treating various pathologies. Combing the pharmacology and systems biology approaches, the network pharmacology (NP) approach was developed to predict the probable mechanism underlying the therapeutic effect of TCM. However, approaches solely based on NP cannot effectively elucidate the curative mechanism in a holistic and reliable manner due to limitations in NP-based methods and complexity of TCM components. Thus, integration strategies combining NP with other approaches are increasingly being used. Since the interdisciplinary research in TCM has received much attention in the advent of the big data era of which the NP-based integration strategy is broadly used, the strategy is clearly elaborated in the present review. We summarized several NP-based integration strategies and their applications in TCM studies, including multi-omics approach, gut microbiota study, chemical information analysis, data-mining, and network toxicology study.

Indexed as

Drugs, Chinese HerbalMedicine, Chinese TraditionalData MiningHumansNetwork PharmacologyDrugs, Chinese HerbalChinese traditionalintegration strategymedicinenetwork pharmacologyreviewtoxicology

Identifiers

PMID35610020
PMCPMC9924699

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.