News
The research topic "Modern Machine Learning Approaches for Quantitative Inference of Gene Regulation from Genomic and Epigenomic Features", in which our Chief AI Scientist, Michael Banf, played a significant role as a guest editor, was recently published in the journal Frontiers in Plant Science.
Edited in collaboration with Kangmei Zhao from the Carnegie Institution for Science and Thomas Hartwig from the Max Planck Institute for Plant Breeding Research, the research topic impressively demonstrates how modern AI technologies can effectively analyze complex biological data. It provides new insights into plant bioinformatics and opens up perspectives for the use of AI in gene regulation.
We would like to thank all those involved, whose expertise and commitment made this success possible. We hope that the articles serve as valuable resources and inspire further research.
For more information, please visit the following link: Frontiers in Plant Science - Guest Editorial.
Event
Liliya Imasheva presented a validation pipeline for evaluating AI summaries at Conf42 Large Language Models 2026.
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At the IOCMA 2026 conference, Perelyn presented our method, which transforms graph data such as supply chains or networks so that AI models can learn more reliably from it, even over long distances.
