Evidence map›Paper›PMID 22326356›Full record

ReviewJournal of ethnopharmacology2012

In-silico studies in Chinese herbal medicines' research: evaluation of in-silico methodologies and phytochemical data sources, and a review of research to date.

D J Barlow, A Buriani, T Ehrman, E Bosisio, I Eberini, P J Hylands

Abstract readEvaluation StudyReview
In one paragraph

Review in Journal of ethnopharmacology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Review
  6. Article
  7. Frontiers in pharmacology · 2023
    Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. An overview on adverse drug reactions to traditional Chinese medicines.British journal of clinical pharmacology · 2015
    Review
  17. Review
  18. Article
  19. Application of transcriptomics in Chinese herbal medicine studies.Journal of traditional and complementary medicine · 2012
    Review
  20. 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

6 authors.

D J BarlowInstitute of Pharmaceutical Science, King's College London, Franklin Wilkins Building, 150 Stamford Street, London SE1 9NH, UK. dave.barlow@kcl.ac.uk
A Buriani
T Ehrman
E Bosisio
I Eberini
P J Hylands

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The available databases that catalogue information on traditional Chinese medicines are reviewed in terms of their content and utility for in-silico research on Chinese herbal medicines, as too are the various protein database resources, and the software available for use in such studies. The software available for bioinformatics and 'omics studies of Chinese herbal medicines are summarised, and a critical evaluation given of the various in-silico methods applied in screening Chinese herbal medicines, including classification trees, neural networks, support vector machines, docking and inverse docking algorithms. Recommendations are made regarding any future in-silico studies of Chinese herbal medicines.

Indexed as

PhytotherapyComputational BiologyDatabases, FactualDatabases, ProteinDrug Evaluation, PreclinicalDrugs, Chinese HerbalGenomicsHerbal MedicineHumansMedicine, Chinese TraditionalPlants, MedicinalResearch DesignSoftwareDrugs, Chinese Herbal

Identifiers

PMID22326356
PMCPMC7126886

What OpenQuestion holds

Textmetadata
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.