The Institute of Biological and Geosciences (IBG) generates high-resolution data every day from sensors, sequencing, imaging, and remote sensing. This data is used to study topics such as microorganisms in soils, material flows in landscapes, and plant growth under climate stress. It forms the basis of innovative AI processes, simulation-based models, and data-driven decisions, which greatly benefit science, society, and the bioeconomy. These processes play a central role in enhancing our understanding of biological systems, environmental processes, and biotechnological processes, as well as in designing them in a sustainable manner.
Simulation and data-driven modeling
As part of the Center for Advanced Simulation and Analytics (CASA) at the Jülich Supercomputing Center (JSC), the IBG collaborates in the Simulation and Data Lab Digital Bioeconomy (SDL-DBE) to develop new methods for simulating and analyzing biological and biotechnological systems using data. The goal is to leverage high-performance computing, multiscale models, AI-powered simulations, and digital workflows to generate new insights in areas such as plant research, microbial systems, and circular biotechnology. In addition, the combination of experimentation and simulation is resulting in tools for resilient processes—for example, in the digital twin project ReGenFarm, which dynamically maps agricultural production systems.
Data Acquisition and Infrastructure
At the IBG, we collect plant, microbial, and environmental data using modern methods. Examples include the GrowScreen with 3D imaging, sequence analysis, environmental sensors, drones, and satellite remote sensing. The Helmholtz Sensor Management System (SMS) supports the efficient and distributed management of large sensor infrastructures. Viewers such as Helmholtz Earth Portal are used to visually display data over time. Connected to national research data infrastructures (NFDI) such as DataPLANT, NFDI4bioimage, NFDI4microbiota, and FAIRagro, this data flows into open infrastructures according to the FAIR principle (findable, accessible, interoperable, reusable). In addition, the IBG coordinates the national infrastructure de.NBI (German Network for Bioinformatics Infrastructure) and its European branch ELIXIR Germany. These networks provide powerful tools and services for the analysis of biological and biotechnological data, as well as a powerful cloud infrastructure. This makes our research data sustainably usable and internationally networked.
Artificial intelligence
The AI-supported analysis of this data, for example to identify spatiotemporal patterns in environmental modeling, is also a key area of work. Whether annotating complex genomes (Helixer), analyzing regulatory elements (deepCRE), predicting protein functions (TopEC, OneProt), or interpreting microbiome data, AI helps to identify patterns that would be virtually invisible to humans. AI is also increasingly being used in remote sensing and environmental modeling (AI Strategy for Earth System Data, KISTE).
