Evidence map›Paper›PMID 26461812›Full record

ReviewEvolutionary bioinformatics online2015

Genomics and Evolution in Traditional Medicinal Plants: Road to a Healthier Life.

Da-Cheng Hao, Pei-Gen Xiao

Abstract readReview
In one paragraph

Review in Evolutionary bioinformatics online, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Natural Compounds ofBiomedicines · 2023
    Review
  10. Article
  11. Article
  12. Hydroethanolic Extract of DefattedMedicines (Basel, Switzerland) · 2021
    Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. Computational and structural biotechnology journal · 2021
    Article
  18. Article
  19. 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

2 authors.

Da-Cheng HaoBiotechnology Institute, School of Environment and Chemical Engineering, Dalian Jiaotong University, Dalian, P. R. China.
Pei-Gen XiaoInstitute of Medicinal Plant Development, Chinese Academy of Medical Sciences, Beijing, P. R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medicinal plants have long been utilized in traditional medicine and ethnomedicine worldwide. This review presents a glimpse of the current status of and future trends in medicinal plant genomics, evolution, and phylogeny. These dynamic fields are at the intersection of phytochemistry and plant biology and are concerned with the evolution mechanisms and systematics of medicinal plant genomes, origin and evolution of the plant genotype and metabolic phenotype, interaction between medicinal plant genomes and their environment, the correlation between genomic diversity and metabolite diversity, and so on. Use of the emerging high-end genomic technologies can be expanded from crop plants to traditional medicinal plants, in order to expedite medicinal plant breeding and transform them into living factories of medicinal compounds. The utility of molecular phylogeny and phylogenomics in predicting chemodiversity and bioprospecting is also highlighted within the context of natural-product-based drug discovery and development. Representative case studies of medicinal plant genome, phylogeny, and evolution are summarized to exemplify the expansion of knowledge pedigree and the paradigm shift to the omics-based approaches, which update our awareness about plant genome evolution and enable the molecular breeding of medicinal plants and the sustainable utilization of plant pharmaceutical resources.

Indexed as

drug discovery and developmentgenome evolutionmedicinal plantsphylogenomicsphylogeny

Identifiers

PMID26461812
PMCPMC4597484

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.