IBG-4: From "Big Data" to biomolecules

Creating, editing, understanding and sharing of complex data: AI and bioinformatics for high-dimensional data and molecular processes in life sciences and bioeconomy.

The institute division Bioinformatics (IBG-4) of the Institute of Bio- and Geosciences (IBG) develops and works on methods, AI and algorithms, aiming for a fundamental understanding of high-dimensional data and processes in life sciences and bioeconomy along with the prediction of the biological function of biomolecules on the basis of their sequences and stuctures leading to their subsequent optimisation for biotechnological and biomedical use. Research in bioinformatics at Forschungszentrum Jülich plays a leading role on national and international level in the area of omics-/data-based bioinformatics focusing on genome analysis, the field of integration, interpretation and visualisation of high-dimensional omics data and plant data management in bioeconomy and in the area of structure-based bioinformatics focusing on understanding, predicting and modulating of the dynamics and interactions of biomolecules. IBG-4 is involved in the development of new methods, AI and algorithms focusing on knowledge management, data integration, sequence and structure-based bioinformatics, machine learning and simulation sciences.

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Omics-/Data-based Bioinformatics

The topic Omics-/Data-based Bioinformatics is headed by Prof. Dr. Björn Usadel. Current research on genomes, transcriptomes, metabolomes and phenotypic analyses generate extensively large and complex data sets. For analysis and interpretation of such data, and AI-based bioinformatic support is essential.

Structure-based Bioinformatics

The topic Structure-based Bioinformatics is headed by Prof. Dr. Holger Gohlke. The group develops and applies computational techniques in the areas of bioinformatics, AI, machine learning and computational biophysics to investigate the contribution of protein structures and dynamics to their function. The main research focus is the fundamental understanding and rational optimization of enzymes for bioeconomy.

NEWS and events

Publication

New AI-based method for the prediction of Enzyme Commission classes

A new study was published in the Nature communications by the Gohlke group in collaboration with Helmholtz AI. This study presents TopEC, a new 3D graph neural network based prediction tool to predict Enzyme Commission (EC) classes.

Publication

Purple to White, Smooth to Prickly: Genetic Diversity of Eggplants Recorded for the First Time

For the very first time, researchers have created a complete catalogue of genes and traits of the eggplant. Their findings pave the way for more robust, climate-adapted, and high-quality varieties that secure long-term crop yields and preserve diversity in agriculture. Jülich scientists were involved in the study along with teams from six other countries.

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Selected recent publications:

Holst, F. ; Bolger, A. M. ; Kindel, F. ; Günther, C. ; Maß, J. ; Triesch, S. ; Kiel, N. ; Saadat, N. ; Ebenhöh, O. ; Usadel, B. ; Schwacke, R. ; Weber, A. P. M. ; Bolger, M. (Corresponding author) ; Denton, A. K.
Helixer: ab initio prediction of primary eukaryotic gene models combining deep learning and a hidden Markov model
Nature methods 23, 732-739 (2026) [10.1038/s41592-025-02939-1]

Gaccione, L. ; Toppino, L. ; Bolger, M. ; Schmidt, M. ; Tassone, M. R. ; Sulli, M. ; Idahl, E. ; Alonso, D. ; Aprea, G. ; Ferrante, P. ; Lefebvre, V. ; Boyaci, H. F. ; Schafleitner, R. ; Gattolin, S. ; Finkers, R. ; Brouwer, M. ; Bovy, A. ; Prohens, J. ; Portis, E. ; Lanteri, S. ; Rotino, G. L. ; Giuliano, G. (Corresponding author) ; Usadel, B. (Corresponding author) ; Barchi, L. (Corresponding author)
Graph-based pangenomes and pan-phenome provide a cornerstone for eggplant biology and breeding
Nature Communications 16(1), 9919 (2025) [10.1038/s41467-025-64866-1]

Zhang, W. ; Tariq, A. ; Jia, X. ; Yan, J. ; Fernie, A. R. (Corresponding author) ; Usadel, B. (Corresponding author) ; Wen, W. (Corresponding author)
Plant sperm cell sequencing for genome phasing and determination of meiotic crossover points
Nature protocols 20, 690–708 (2025) [10.1038/s41596-024-01063-2]

van der Weg, K. ; Merdivan, E. ; Piraud, M. ; Gohlke, H. (Corresponding author)
TopEC: prediction of Enzyme Commission classes by 3D graph neural networks and localized 3D protein descriptor
Nature Communications 16(1), 2737 (2025) [10.1038/s41467-025-57324-5]

Peleke, F. F. ; Zumkeller, S. M. ; Gültas, M. ; Schmitt, A. ; Szymański, J. (Corresponding author)
Deep learning the cis-regulatory code for gene expression in selected model plants
Nature Communications 15(1), 3488 (2024) [10.1038/s41467-024-47744-0]

Marasco, R. ; Fusi, M. ; Coscolín, C. ; Barozzi, A. ; Almendral, D. ; Bargiela, R. ; Nutschel, C. G. n. ; Pfleger, C. ; Dittrich, J. ; Gohlke, H. ; Matesanz, R. ; Sanchez-Carrillo, S. ; Mapelli, F. ; Chernikova, T. N. ; Golyshin, P. N. ; Ferrer, M. (Corresponding author) ; Daffonchio, D. (Corresponding author)
Enzyme adaptation to habitat thermal legacy shapes the thermal plasticity of marine microbiomes
Nature Communications 14(1), 1045 (2023) [10.1038/s41467-023-36610-0]

Borggräfe, J. ; Victor, J. ; Rosenbach, H. ; Viegas, A. ; Gertzen, C. G. W. ; Wuebben, C. ; Kovacs, H.; Gopalswamy, M. ; Riesner, D. ; Steger, G.; Schiemann, O. ; Gohlke, H. ; Span, I. ; Etzkorn, M. (Corresponding author)
Time-resolved structural analysis of an RNA-cleaving DNA catalyst
Nature 601, 144-149 (2022) [10.1038/s41586-021-04225-4]

Moe-Lange, J. (Corresponding author) ; Gappel, N. M. ; Machado, M. ; Wudick, M. M. ; Sies, C. S. A. ; Schott, S. ; Bonus, M. ; Mishra, S. ; Hartwig, T. ; Bezrutczyk, M. ; Basu, D. ; Farmer, E. E. ; Gohlke, H. ; Malkovskiy, A. ; Haswell, E. S. ; Lercher, M. J. ; Ehrhardt, D. W. ; Frommer, W. B. (Corresponding author) ; Kleist, T. J.
Interdependence of a mechanosensitive anion channel and glutamate receptors in distal wound signaling
Science advances 7(37), eabg4298 (2021) [10.1126/sciadv.abg4298]

Harris, A. ; Wagner, M. ; Du, D. ; Raschka, S. ; Nentwig, L.-M. ; Gohlke, H. ; Smits, S. H. J. ; Luisi, B. F. (Corresponding author) ; Schmitt, L. (Corresponding author)
Structure and efflux mechanism of the yeast pleiotropic drug resistance transporter Pdr5
Nature Communications 12(1), 5254 (2021) [10.1038/s41467-021-25574-8]

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