Evidence map›Paper›PMID 19478073›Full record

ReviewPlant & cell physiology2009

Functional analysis of transcription factors in Arabidopsis.

Nobutaka Mitsuda, Masaru Ohme-Takagi

Open access · bronzeAbstract readReview
In one paragraph

Review in Plant & cell physiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 papers.

0numbers the graph read from it
0cells of the map it votes in
137citing papers in PubMed
22.3field-weighted citation impact, top 1% 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

137 citing papers in PubMed, 296 citations in OpenAlex.

  1. Article
  2. Artificial Intelligence for Plant Gene Regulatory Networks.International journal of molecular sciences · 2026
    Review
  3. Article
  4. Design and Testing of Root-Specific Synthetic Promoters by Machine Learning.International journal of molecular sciences · 2026
    Article
  5. Article
  6. Jasmonic Acid Signals Involved inCurrent issues in molecular biology · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Identification ofPlants (Basel, Switzerland) · 2024
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Genome-Wide Identification and Expression Analysis ofInternational journal of molecular sciences · 2024
    Article
  18. Article
  19. Article
  20. Article

77 more citing papers are in PubMed but not listed here.

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 at 1 institution in 1 country.

Nobutaka MitsudaResearch Institute of Genome-Based Biofactory, National Institute of Advanced Industrial Science and Technology (AIST), Central 4, Higashi, Tsukuba, Japan.
Masaru Ohme-Takagi
National Institute of Advanced Industrial Science and Technology · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcription factors (TFs) regulate the expression of genes at the transcriptional level. Modification of TF activity dynamically alters the transcriptome, which leads to metabolic and phenotypic changes. Thus, functional analysis of TFs using 'omics-based' methodologies is one of the most important areas of the post-genome era. In this mini-review, we present an overview of Arabidopsis TFs and introduce strategies for the functional analysis of plant TFs, which include both traditional and recently developed technologies. These strategies can be assigned to five categories: bioinformatic analysis; analysis of molecular function; expression analysis; phenotype analysis; and network analysis for the description of entire transcriptional regulatory networks.

Indexed as

ArabidopsisArabidopsis ProteinsComputational BiologyDatabases, GeneticGene Expression ProfilingGene Expression Regulation, PlantGene Regulatory NetworksPhenotypeRNA, PlantTranscription FactorsArabidopsis ProteinsRNA, PlantTranscription Factors

Identifiers

PMID19478073
PMCPMC2709548
OpenAlexW2130472562

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.