Understanding what plant genes do is essential for tackling global food security, sustainable agriculture, and environmental change. When we know a gene’s function, we can use that knowledge to improve crops by increasing disease resistance, lowering the energy cost of growth, or reducing the need for fertilisers. Yet for most plant genes, we still lack clear functional information. This “gene knowledge gap” limits how efficiently we can design crops that are resilient, productive, and sustainable.
My research vision is to establish KU/PLEN as an international reference environment for reliable and interpretable plant gene function discovery. The long-term goal is to move from “lists of candidate genes” to actionable biological understanding by combining three types of evidence: (i) patterns in large-scale datasets (such as gene expression across tissues and conditions), (ii) direct evidence from the scientific literature, and (iii) evolutionary comparisons across many plant species. I use computational methods and AI to integrate these sources into predictions that are transparent and testable, linking each predicted function to supporting data and publications, and highlighting where functions are conserved across plants or have evolved in specific lineages.
