Evidence map›Paper›PMID 28769804›Full record

ReviewFrontiers in pharmacology2017

Metabolomics and Integrative Omics for the Development of Thai Traditional Medicine.

Sakda Khoomrung, Kwanjeera Wanichthanarak, Intawat Nookaew, Onusa Thamsermsang, Patcharamon Seubnooch, Tawee Laohapand, Pravit Akarasereenont

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

17 citing papers in PubMed, 42 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Mass spectrometry-based analysis of gut microbial metabolites of aromatic amino acids.Computational and structural biotechnology journal · 2023
    Review
  6. Article
  7. Mechanistic Wound Healing and Antioxidant Potential ofAntioxidants (Basel, Switzerland) · 2022
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Review
  14. Review
  15. Deep metabolome: Applications of deep learning in metabolomics.Computational and structural biotechnology journal · 2020
    Review
  16. Article
  17. 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 3 countries.

Sakda KhoomrungCenter of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol UniversityBangkok, Thailand.
Kwanjeera WanichthanarakCenter of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol UniversityBangkok, Thailand.
Intawat NookaewCenter of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol UniversityBangkok, Thailand.
Onusa ThamsermsangCenter of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol UniversityBangkok, Thailand.
Patcharamon SeubnoochDepartment of Pharmacology, Faculty of Medicine Siriraj Hospital, Mahidol UniversityBangkok, Thailand.
Tawee LaohapandCenter of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol UniversityBangkok, Thailand.
Pravit AkarasereenontCenter of Applied Thai Traditional Medicine, Faculty of Medicine Siriraj Hospital, Mahidol UniversityBangkok, Thailand.
Siriraj Hospital · THMahidol University · THChalmers University of Technology · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, interest in studies of traditional medicine in Asian and African countries has gradually increased due to its potential to complement modern medicine. In this review, we provide an overview of Thai traditional medicine (TTM) current development, and ongoing research activities of TTM related to metabolomics. This review will also focus on three important elements of systems biology analysis of TTM including analytical techniques, statistical approaches and bioinformatics tools for handling and analyzing untargeted metabolomics data. The main objective of this data analysis is to gain a comprehensive understanding of the system wide effects that TTM has on individuals. Furthermore, potential applications of metabolomics and systems medicine in TTM will also be discussed.

Indexed as

analytical chemistryherbal medicinesintegrative omicsmetabolomicsThai traditional medicine

Identifiers

PMID28769804
PMCPMC5513896
OpenAlexW2735559031

What OpenQuestion holds

Textmetadata
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.