Evidence map›Paper›PMID 22366161›Full record

ArticleThe Plant cell2012

New technologies for 21st century plant science.

David W Ehrhardt, Wolf B Frommer

Abstract read
In one paragraph

Article in The Plant cell, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. A Systematic Review of Cardio-Metabolic Properties ofAntioxidants (Basel, Switzerland) · 2024
    Review
  3. Article
  4. Spinach-based RNA mimicking GFP in plant cells.Functional & integrative genomics · 2022
    Article
  5. Article
  6. Dynamics and Endocytosis of Flot1 inInternational journal of molecular sciences · 2020
    Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Phenotyping in Plants. Preface.Journal of experimental botany · 2015
    Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Plant proteomics in India and Nepal: current status and challenges ahead.Physiology and molecular biology of plants : an international journal of functional plant biology · 2013
    Review
  18. Article
  19. Article
  20. Review
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.

David W EhrhardtDepartment of Plant Biology, Carnegie Institution for Science, Stanford, California 94305, USA.
Wolf B Frommer

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plants are one of the most fascinating and important groups of organisms living on Earth. They serve as the conduit of energy into the biosphere, provide food, and shape our environment. If we want to make headway in understanding how these essential organisms function and build the foundation for a more sustainable future, then we need to apply the most advanced technologies available to the study of plant life. In 2009, a committee of the National Academy highlighted the "understanding of plant growth" as one of the big challenges for society and part of a new era which they termed "new biology." The aim of this article is to identify how new technologies can and will transform plant science to address the challenges of new biology. We assess where we stand today regarding current technologies, with an emphasis on molecular and imaging technologies, and we try to address questions about where we may go in the future and whether we can get an idea of what is at and beyond the horizon.

Indexed as

Computational BiologyPlantsCell BiologyGenomicsImaging, Three-DimensionalMass SpectrometryMicroscopyPlant DevelopmentScienceSequence Analysis, DNA

Identifiers

PMID22366161
PMCPMC3315222

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.