Evidence map›Paper›PMID 38540375›Full record

ArticleGenes2024

Identification of Salt-Sensitive and Salt-Tolerant Genes through Weighted Gene Co-Expression Networks across Multiple Datasets: A Centralization and Differential Correlation Analysis.

Pajaree Sonsungsan, Apichat Suratanee, Teerapong Buaboocha, Supachitra Chadchawan, Kitiporn Plaimas

Open access · goldAbstract read
In one paragraph

Article in Genes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. 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

5 authors at 2 institutions in 1 country.

Pajaree SonsungsanProgram in Bioinformatics and Computational Biology, Graduate School, Chulalongkorn University, Bangkok 10330, Thailand.
Apichat SurataneeDepartment of Mathematics, Faculty of Applied Science, King Mongkut's University of Technology North Bangkok, Bangkok 10800, Thailand.ORCID 0000-0002-3439-6619
Teerapong BuaboochaCenter of Excellence in Molecular Crop, Department of Biochemistry, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand.
Supachitra ChadchawanCenter of Excellence in Environment and Plant Physiology (CEEPP), Department of Botany, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand.
Kitiporn PlaimasOmics Science and Bioinformatics Center, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand.ORCID 0000-0002-0416-8316
Chulalongkorn University · THKing Mongkut's University of Technology North Bangkok · TH

Funding

National Science, Research and Innovation Fund (NSRF), and King Mongkut's University of Technology North Bangkok KMUTNB-FF-66-08Network Strengthening Fund - Program 16 B16F640103
6 · The paper itself

Abstract

Salt stress is a significant challenge that severely hampers rice growth, resulting in decreased yield and productivity. Over the years, researchers have identified biomarkers associated with salt stress to enhance rice tolerance. However, the understanding of the mechanism underlying salt tolerance in rice remains incomplete due to the involvement of multiple genes. Given the vast amount of genomics and transcriptomics data available today, it is crucial to integrate diverse datasets to identify key genes that play essential roles during salt stress in rice. In this study, we propose an integration of multiple datasets to identify potential key transcription factors. This involves utilizing network analysis based on weighted co-expression networks, focusing on gene-centric measurement and differential co-expression relationships among genes. Consequently, our analysis reveals 86 genes located in markers from previous meta-QTL analysis. Moreover, six transcription factors, namely

Indexed as

OryzaGene Expression ProfilingSalt StressSalt ToleranceTranscription FactorsTranscription Factorsco-expression networksnetwork analysisrice salt stresssalt-sensitive ricesalt tolerancesalt-tolerant riceWGCNA

Identifiers

PMID38540375
PMCPMC10970189
OpenAlexW4392240457

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.