Modern life sciences generate enormous volumes of data, ranging from genome sequences and metabolic profiles to imaging and environmental datasets. A new infrastructure initiative coordinated by the Leibniz Institute of Plant Biochemistry (IPB) will enable researchers to harness artificial intelligence to analyze this wealth of information and unlock new insights into biological systems, from individual proteins and metabolic pathways to complex ecosystems and agricultural landscapes.
The Leibniz Institute of Plant Biochemistry (IPB) in Halle, together with nine other Leibniz institutes, will establish a powerful new AI infrastructure for life sciences. The project, entitled “High-Tech Phenotyping in the Life Sciences,” has been selected by the Leibniz Association for inclusion in a funding initiative of the German Federal Ministry for Research, Technology and Space. The program supports investments in cutting-edge research infrastructures and is designed to attract outstanding international scientists. Conceived as a contribution to Germany’s High-Tech Agenda, the new infrastructure will create a globally competitive research environment for data-intensive science. The project will receive €5 million in funding.
At the core of the initiative is a state-of-the-art GPU cluster designed to train advanced AI models for life science applications. Just as large language models can identify patterns and relationships in vast bodies of text, these new AI models will be able to uncover hidden connections across diverse biological data domains. The research projects of the participating Leibniz partners focus on phenotyping, the systematic measurement and characterization of observable traits in biological systems. To achieve this, researchers will integrate and analyze large, highly heterogeneous datasets spanning genomics, proteomics, metabolomics, imaging, and the environment. The underlying data may reach several petabytes in size, equivalent to the storage capacity required for hundreds of thousands of high-resolution feature films.
Using advanced AI models, the researchers aim to reveal links between genetic makeup, biochemical characteristics, and environmental conditions, opening entirely new avenues of biological discovery. The overarching goal is to gain a deeper understanding of biological processes across every level of life. To make this possible, next-generation AI models will jointly analyze these different types of biological data and place them into a unified context. In this way, biological datasets will effectively be able to “learn to talk to each other,” exposing relationships and patterns that remained hidden until now.
As the coordinating institution, IPB contributes its expertise in the analysis of plant and microbial natural products, multi-omics technologies, and AI-supported interpretation of complex biological data. “The volume of data and the complexity of biological research have reached a scale that can only be fully explored with the help of artificial intelligence,” says Prof. Alain Tissier, Managing Director of the IPB. “With this new infrastructure, we are creating the conditions to systematically analyze these datasets and derive new biological knowledge from them. For plant research at the IPB, this opens up exciting opportunities to gain a much deeper understanding of the origin and functioning of natural compounds, adaptation to environmental conditions, and the evolution of plant metabolic pathways.”
The new infrastructure will provide a shared technological foundation for data-intensive research across the life sciences. Beyond accelerating the development of innovative AI methods, it is expected to make the participating institutions even more attractive destinations for leading researchers from around the world. In the long term, the technologies developed through the initiative are expected to enable new applications in plant science, biotechnology, agriculture, environmental research, and health sciences, thereby contributing to a more sustainable bioeconomy.
The consortium coordinated by IPB brings together the German Primate Center (DPZ), the German Collection of Microorganisms and Cell Cultures (DSMZ), the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), the Leibniz Institute for the Analysis of Biodiversity Change (LIB), the Leibniz Institute for Neurobiology (LIN), the Leibniz Institute of Virology (LIV), the Leibniz Centre for Agricultural Landscape Research (ZALF), and the Leibniz Centre for Tropical Marine Research (ZMT). Associated partners include the Göttingen Academy of Scientific Computing (GWDG), the German Network for Bioinformatics Infrastructure (de.NBI), and the Leibniz Center for Informatics (LZI). The initiative is one of three projects through which the Leibniz Association aims to drive the strategic expansion of AI infrastructures in Germany. The IPB-led effort brings together expertise from life, environmental, and agricultural sciences. Despite their diverse research focuses, the participating institutions are united by the challenge of analyzing ever-larger and more complex biological datasets. Together with two additional initiatives in health research as well as materials science and process engineering, the proposed Leibniz portfolio represents a total investment of approximately €15 million.
Reference: https://www.ipb-halle.de/en/article/ai-infrastructure-life-sciences-high-tech-phenotyping