Co-Expression Networks in Sunflower: Harnessing the Power of Multi-Study Transcriptomic Public Data to Identify and Categorize Candidate Genes for Fungal Resistance.
WRKY
candidate genes
co-expression networks
fungal pathogens
meta-analysis
multi-study analysis
plant pathology
sunflower
transcriptomics
Journal
Plants (Basel, Switzerland)
ISSN: 2223-7747
Titre abrégé: Plants (Basel)
Pays: Switzerland
ID NLM: 101596181
Informations de publication
Date de publication:
25 Jul 2023
25 Jul 2023
Historique:
received:
23
06
2023
revised:
19
07
2023
accepted:
21
07
2023
medline:
12
8
2023
pubmed:
12
8
2023
entrez:
12
8
2023
Statut:
epublish
Résumé
Fungal plant diseases are a major threat to food security worldwide. Current efforts to identify and list
Identifiants
pubmed: 37570920
pii: plants12152767
doi: 10.3390/plants12152767
pmc: PMC10421300
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : National Agency for the Promotion of Research, Technological Development and Innovation, Ministry of Science, Technology and Innovation
ID : PICT 2018-03810; PICT 2019-1698; PICT 2017-1021.
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