AI decodes the language of genes

19/06/2026 Research

An international research team led by CEPLAS researcher Jędrzej Szymański has developed an AI model that improves the prediction of gene regulation in plants.

An international research team led by the IPK Leibniz Institute and Forschungszentrum Jülich has developed an AI model that predicts binding sites of regulatory proteins on plant DNA. The model, trained using data from Arabidopsis thaliana, can also be applied to crop plants and helps to better understand the influence of genetic variation on their performance. The study was published in “Nature Communications”.

Press release from IPK Leibniz Institute

Original publication:

Peleke FF, Zumkeller SM, Schirmer D, Schmitz G, Hartwig T, Engelhorn J, Weizel S, Schmitt AO, Jores T, Szymanski J (2026) Genome-wide modelling of plant transcription factor binding captures regulatory variants associated with phenotypic traits. Nat Commun 17(1). DOI: 10.1038/s41467-026-73634-8
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