Summary
The convergence of high-resolution multi-omics technologies with computational systems biology is transforming plant physiology by enabling predictive, mechanistic, and field-relevant insights into crop performance, adaptation, and resilience. This review presents an integrative and forward-looking synthesis spanning genomics, transcriptomics, proteomics, metabolomics, epigenomics, phenomics, and the rapidly emerging fields of single-cell and spatial omics, highlighting how these complementary layers can be computationally unified to achieve cell-type-resolved and tissue-specific insights into plant function. We discuss integrative analytical frameworks that combine gene regulatory network inference, machine learning, and explainable artificial intelligence (XAI), illustrating how these ap
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