Evidence map›Paper›PMID 26719053›Full record

ReviewPlanta2016

Bioinformatic landscapes for plant transcription factor system research.

Yijun Wang, Wenjie Lu, Dexiang Deng

Abstract readReview
PubMed Publisher
In one paragraph

Review in Planta, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.1field-weighted citation impact, top 11% 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

5 citing papers in PubMed, 16 citations in OpenAlex.

  1. Plants (Basel, Switzerland) · 2024
    Article
  2. Transcriptome analyses reveal the expression profile of genes related to lignan biosynthesis inPhysiology and molecular biology of plants : an international journal of functional plant biology · 2022
    Article
  3. Article
  4. Article
  5. Transcriptome Analysis of theFrontiers in plant science · 2016
    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

3 authors at 1 institution in 1 country.

Yijun WangJiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Key Laboratory of Plant Functional Genomics of the Ministry of Education, Yangzhou University, Yangzhou, 225009, China. wyj@yzu.edu.cn.
Wenjie LuJiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Key Laboratory of Plant Functional Genomics of the Ministry of Education, Yangzhou University, Yangzhou, 225009, China.
Dexiang DengJiangsu Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops, Key Laboratory of Plant Functional Genomics of the Ministry of Education, Yangzhou University, Yangzhou, 225009, China.
Yangzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MAIN

conclusionDiverse bioinformatic resources have been developed for plant transcription factor (TF) research. This review presents the bioinformatic resources and methodologies for the elucidation of plant TF-mediated biological events. Such information is helpful to dissect the transcriptional regulatory systems in the three reference plants Arabidopsis , rice, and maize and translation to other plants. Transcription factors (TFs) orchestrate diverse biological programs by the modulation of spatiotemporal patterns of gene expression via binding cis-regulatory elements. Advanced sequencing platforms accompanied by emerging bioinformatic tools revolutionize the scope and extent of TF research. The system-level integration of bioinformatic resources is beneficial to the decoding of TF-involved networks. Herein, we first briefly introduce general and specialized databases for TF research in three reference plants Arabidopsis, rice, and maize. Then, as proof of concept, we identified and characterized heat shock transcription factor (HSF) members through the TF databases. Finally, we present how the integration of bioinformatic resources at -omics layers can aid the dissection of TF-mediated pathways. We also suggest ways forward to improve the bioinformatic resources of plant TFs. Leveraging these bioinformatic resources and methodologies opens new avenues for the elucidation of transcriptional regulatory systems in the three model systems and translation to other plants.

Indexed as

Computational BiologyDatabases, GeneticGene Expression Regulation, PlantPlant ProteinsPlantsTranscription FactorsTranscriptomePlant ProteinsTranscription FactorsBioinformatics-omicsPlant transcription factorsSystems biology

Identifiers

PMID26719053
OpenAlexW2199044663

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.