Publications of the group Biochemical Network Analysis
Showing entries 1 - 10 out of 61
2026
Economic Cell Collective, Szeliova, D., & Müller, S. (2026). Economic Principles in Cell Biology. https://doi.org/10.5281/zenodo.18088026
Kushwaha, M., Liebermeister, W., Noor, E., Sechkar, K., & Szeliova, D. (2026). Benefit and cost of a protein. In Economic Principles in Cell Biology (Textbook ) https://doi.org/10.5281/zenodo.18087995
2025
Karasová, M., Jobst, M., Framke, D., Bergen, J., Meier-Menches, S., Keppler, B., Koellensperger, G., Zanghellini, J., Gerner, C., & Del Favero, G. (2025). Mechanical cues rewire lipid metabolism and support chemoresistance in epithelial ovarian cancer cell lines OVCAR3 and SKOV3. Cell communication and signaling, 23(1), Article 193. https://doi.org/10.1186/s12964-025-02144-9
Zehetner, L., Széliová, D., Kraus, B., Hernandez Bort, J. A., & Zanghellini, J. (2025). Multi-omics driven genome-scale metabolic modeling improves viral vector yield in HEK293. Metabolic engineering, 91, 103-118. https://doi.org/10.1016/j.ymben.2025.03.011
Graf, A. C., Libiseller-Egger, J., Gotsmy, M., & Zanghellini, J. (2025). Fedbatchdesigner: A User-Friendly Dashboard for Modeling and Optimizing Growth-Arrested Fed-Batch Processes. ACS Synthetic Biology, 14(8), 3252-3257. https://doi.org/10.1021/acssynbio.5c00357
Klamt, S., Zanghellini, J., & Von Kamp, A. (2025). Minimal cut sets in metabolic networks: From conceptual foundations to applications in metabolic engineering and biomedicine. Briefings in bioinformatics, 26(2), Article bbaf188. https://doi.org/10.1093/bib/bbaf188
Lázaro, J., Joven, T., Széliová, D., Zanghellini, J., & Júlvez, J. (2025). Multi-scale design and optimization of antibody production via flexible nets. Computational and Structural Biotechnology Journal, 27, 1498-1510. https://doi.org/10.1016/j.csbj.2025.03.040
Grigaitis, P., & Szeliova, D. (2025). An inventory of cell components. In Economic Principles in Cell Biology (Textbook ) https://doi.org/10.5281/zenodo.14562695
2024
Széliová, D., Müller, S., & Zanghellini, J. (2024). Costs of ribosomal RNA stabilization affect ribosome composition at maximum growth rate. Communications Biology, 7(1), Article 196. https://doi.org/10.1038/s42003-024-05815-4
Schlögel, G., Lück, R., Kittler, S., Spadiut, O., Kopp, J., Zanghellini, J., & Gotsmy, M. (2024). Optimizing bioprocessing efficiency with OptFed: Dynamic nonlinear modeling improves product-to-biomass yield. Computational and Structural Biotechnology Journal, 23, 3651-3661. https://doi.org/10.1016/j.csbj.2024.09.024
Activities of the group Biochemical Network Analysis
Showing entries 51 - 60 out of 135
Structural and functional interpretation of crosslink intensities
Stefanie Brandstetter
,
Benjamin Neuditschko
,
Franz Herzog
,
Jürgen Zanghellini
4<sup>th</sup> International DoSChem Student Symposium
Conference,
Poster presentation
12.9.2024 - 12.9.2024
Comprehensive theory of (microbial) community growth in constraint-based modeling
Diana Szeliova
,
Müller Stefan
,
Marianne Mießkes
,
Jürgen Zanghellini
10th IFAC International Conference on Foundations of Systems Biology in Engineering (FOSBE 2024)
Conference,
Poster presentation
8.9.2024 - 8.9.2024
Optimizing Fed-Batch Processes with Dynamic Control Flux Balance Analysis
Mathias Gotsmy
,
Dafni Giannari
,
Radhakrishnan Mahadevan
,
Jürgen Zanghellini
10th IFAC International Conference on Foundations of Systems Biology in Engineering (FOSBE 2024)
Conference,
Poster presentation
8.9.2024 - 8.9.2024
An inventory of cell components
Diana Szeliova
,
Pranas Grigaitis
Summer school “Economic Principles in Cell Biology”
Summer/Winter school,
Talk or oral contribution
8.7.2024 - 8.7.2024
Precision Modeling for Bioprocess Optimization
Mathias Gotsmy
,
Guido Schlögel
,
Dafni Giannari
,
Rüdiger Lück
,
Anna Erian
,
Stefan Kittler
,
Oliver Spadiut
,
Julian Kopp
,
Hans Marx
,
Stefan Pflügl
,
Radhakrishnan Mahadevan
,
Jürgen Zanghellini
Austrian Bioinformatics Workshop 2024
Seminar/Workshop,
Poster presentation
3.7.2024 - 3.7.2024
Structural and functional interpretation of crosslink intensities
Stefanie Brandstetter
,
Benjamin Neuditschko
,
Franz Herzog
,
Jürgen Zanghellini
Summer school in bioinformatics
Summer/Winter school,
Poster presentation
17.6.2024 - 17.6.2024
Logistic PCA explains differences between genome-scale metabolic models in terms of metabolic pathways
Leopold Zehetner
,
Diana Szeliova
,
Barbara Kraus
,
Juan A. Hernandez Bort
,
Jürgen Zanghellini
9<sup>th</sup> international conference on Systems Biology of Mammalian Cells SBMC 2024
Conference,
Poster presentation
13.5.2024 - 13.5.2024
Designing an optimal fed-batch process using a comprehensive differential equation model
Guido Schlögel
,
Mathias Gotsmy
,
Jürgen Zanghellini
Vienna Doctoral School in Chemistry: Panel B: Retreat 2024
Seminar/Workshop,
Poster presentation
24.4.2024 - 24.4.2024
PyCoMo transparently facilitates creating and studying community metabolic models
Marianne Mießkes
,
Michael Predl
,
Thomas Rattei
,
Jürgen Zanghellini
Vienna Doctoral School in Chemistry: Panel B: Retreat 2024
Seminar/Workshop,
Poster presentation
24.4.2024 - 24.4.2024
Structural and functional interpretation of crosslink intensities
Stefanie Brandstetter
,
Benjamin Neuditschko
,
Franz Herzog
,
Jürgen Zanghellini
Vienna Doctoral School in Chemistry: Panel B: Retreat 2024
Seminar/Workshop,
Poster presentation
24.4.2024 - 24.4.2024
Showing entries 51 - 60 out of 135
Projects of the group Biochemical Network Analysis
Showing entries 1 - 4 out of 4
Morpho-metabolischer Fingerabdruck von Ovarialkarzinom
Del Favero, G. (Project Lead), Köllensperger, G. (Co-Lead), Gerner, C. (Co-Lead) & Zanghellini, J. (Co-Lead)
15/09/22 → 14/09/27
Project: Research funding
Prokaryote proteomics at high temperature for single cells
Zanghellini, J. (Project Lead)
1/01/24 → 31/12/27
Project: Research cooperation
Circular Bioengineering
Köllensperger, G. (Project Lead), Ludwig, R. (Co-Lead), Bismarck, A. (Co-Lead), Zanghellini, J. (Co-Lead) & Woodward, R. (Co-Lead)
1/12/24 → 30/11/29
Project: Research funding
Fungi in museums and collections: a novel, highly sensitive, AI powered sensor system for the early stage detection of fungal contaminations
Zanghellini, J. (Project Lead), Sterflinger , K. (Co-Lead) & Kellner , E. (Co-Lead)
1/04/26 → 31/03/29
Project: Research funding
Showing entries 1 - 4 out of 4