Uncovering waterlogging-responsive genes in cucumber through machine learning and differential gene correlation analysis
Abstract As climate change intensifies, the frequency and severity of waterlogging are expected to increase, necessitating a deeper understanding of the cucumber response to this stress. In this study, three public RNA-seq datasets (PRJNA799460, PRJNA844418, and PRJNA678740) comprising 36 samples we...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2024-08-01
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| Series: | Botanical Studies |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40529-024-00433-z |