Evidence map›Paper›PMID 34603473›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2021

TCDO: A Community-Based Ontology for Integrative Representation and Analysis of Traditional Chinese Drugs and Their Properties.

Yan Zhu, Lihong Liu, Bo Gao, Jing Liu, Xingchao Qiao, Chaojie Lian, Yongqun He

Open access · hybridAbstract read
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 50% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. 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

7 authors at 3 institutions in 2 countries.

Yan ZhuInstitute of Information on Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.ORCID https://orcid.org/0000-0002-5592-8258
Lihong LiuInstitute of Information on Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.
Bo GaoInstitute of Information on Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.
Jing LiuInstitute of Information on Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.
Xingchao QiaoInstitute of Information on Traditional Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing 100700, China.
Chaojie LianNational Institutes for Food and Drug Control, Beijing 102627, China.ORCID https://orcid.org/0000-0001-8678-2709
Yongqun HeUniversity of Michigan Medical School, Ann Arbor, MI 48109, USA.ORCID https://orcid.org/0000-0001-9189-9661
Chinese Academy of Medical Sciences & Peking Union Medical College · CNNational Institutes for Food and Drug Control · CNUniversity of Michigan · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional Chinese drugs (TCDs) have been widely used in clinical practice in China and many other regions for thousands of years. Nowadays TCD's bioactive ingredients and mechanisms of action are being identified. However, the lack of standardized terminologies or ontologies for the description of TCDs has hindered the interoperability and deep analysis of TCD knowledge and data. By aligning with the Basic Formal Ontology (BFO), an ISO-approved top-level ontology, we constructed a community-driven TCD ontology (TCDO) with the aim of supporting standardized TCD representation and integrated analysis. TCDO provides logical and textual definitions of TCDs, TCD categories, and the properties of TCDs (i.e., nature, flavor, toxicity, and channel tropism). More than 400 popular TCD decoction pieces (TCD-DPs) and Chinese medicinal materials (CMMs) are systematically represented. The logical TCD representation in TCDO supports computer-assisted reasoning and queries using tools such as Description Logic (DL) and SPARQL queries. Our statistical analysis of the knowledge represented in TCDO revealed scientific insights about TCDs. A total of 36 TCDs with medium or high toxicity are most densely distributed, primarily in

Identifiers

PMID34603473
PMCPMC8483929
OpenAlexW3201416135

What OpenQuestion holds

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LicenceCC BY
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.