Phenotype prediction in plants is improved by integrating large-scale transcriptomic datasets.

Abstract excerpt

Research on the dynamic expression of genes in plants is important for understanding different biological processes. We used the large amounts of transcriptomic data from various plant sample sources that are publicly available to investigate whether the expression levels of a subset of highly variable genes (HVGs) can be used to accurately identify the phenotypes of plants. Using maize (Zea mays L.) as an...

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• Databases, Genetic
• Gene Expression Profiling
• Gene Expression Regulation, Plant
• Machine Learning
• Oryza