ai-in-biology
AI in biology refers to the application of machine learning, deep learning, and other artificial intelligence techniques to analyze complex biological data, identify patterns, and generate predictive models across living systems. In plant science, AI accelerates breakthroughs by enabling researchers to process vast genomic, phenotypic, and environmental datasets—tasks that would be intractable by hand—to uncover gene functions, predict crop performance, and model plant responses to climate stress. These capabilities are transforming fields from precision agriculture to evolutionary biology, making AI an increasingly essential tool for understanding and improving plant life.
PubMed · 2026-04-01
Scientists can now read plant DNA more completely than ever before, producing near-perfect blueprints of entire plant genomes — even for complex plants with multiple copies of their chromosomes. The next challenge is figuring out what all those genes actually do.
New sequencing technologies now enable complete, gap-free plant genome assemblies from one chromosome end to the other, even for complex polyploid species like wheat that carry multiple genome copies.
The bottleneck in plant genomics has shifted from building genome maps to interpreting them — annotating what each gene does remains the field's greatest challenge and opportunity.
AI-powered gene prediction tools and large language models are beginning to automate the entire workflow from DNA extraction to functional gene annotation, promising a major leap in speed and accuracy.