Dr. M. (Matteo) Barberis
Faculty of Science
Swammerdam Institute for Life Sciences
Visiting address
- Science Park 904
Postal address
- Postbus 1212
1000 BE Amsterdam
Contact details
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Publications
2021
- Barberis, M. (2021). A multi-approach and multi-scale platform to model CD4+ T cells responding to infections. Npj Systems Biology and Applications.
- Barberis, M. (2021). Integrative computational approach identifies drug targets in CD4+ T-cell-mediated immune disorders. Npj Systems Biology and Applications.
- Barberis, M. (2021). Quantitative model of eukaryotic Cdk control through the Forkhead CONTROLLER. Npj Systems Biology and Applications.
- Barberis, M. (2021). Sirtuins-Mediated System-Level Regulation of Mammalian Tissues at the Interface between Metabolism and Cell Cycle: A Systematic Review. Biology (Basel), 10(3). https://doi.org/10.3390/biology10030194
- Barberis, M. (2021). SysMod: the ISCB community for data-driven computational modelling and multi-scale analysis of biological systems. Bioinformatics.
- Barberis, M., Westerhoff, H. V., Verstegen, N. J. M. C., & van Ham, S. M. (2021). System-Level Scenarios for the Elucidation of T Cell-Mediated Germinal Center B Cell Differentiation. Frontiers in Immunology.
2020
Abudukelimu, A., Barberis, M., Redegeld, F., Sahin, N., Sharma, R. P., & Westerhoff, H. V. (2020). Complex Stability and an Irrevertible Transition Reverted by Peptide and Fibroblasts in a Dynamic Model of Innate Immunity. Frontiers in Immunology, 10, [3091]. https://doi.org/10.3389/fimmu.2019.03091 [details]- Barberis, M. (2020). Computer-Aided Whole-Cell Design: Taking a Holistic Approach by Integrating Synthetic With Systems Biology. Frontiers in Bioengineering and Biotechnology.
- Barberis, M. (2020). Synthetic designs regulating cellular transitions: Fine-tuning of switches and oscillators. Current Opinion in Systems Biology.
- Kolodkin, A. N., Sharma, R. P., Colangelo, A. M., Ignatenko, A., Martorana, F., Jennen, D., Briedé, J. J., Brady, N., Barberis, M., Mondeel, T. D. G. A., Papa, M., Kumar, V., Peters, B., Skupin, A., Alberghina, L., Balling, R., & Westerhoff, H. V. (2020). ROS networks: Designs, aging, Parkinson's disease and precision therapies. Npj Systems Biology and Applications, 6, [34]. https://doi.org/10.1038/s41540-020-00150-w [details]
- Mondeel, T. D. G. A., Ivanov, O., Westerhoff, H. V., Liebermeister, W., & Barberis, M. (2020). Clb3-centered regulations are recurrent across distinct parameter regions in minimal autonomous cell cycle oscillator designs. Npj Systems Biology and Applications, 6, [8]. https://doi.org/10.1038/s41540-020-0125-0 [details]
2019
- Barberis, M., & Mondeel, D. G. A. (2019). ChIP-exo analysis highlights Fkh1 and Fkh2 transcription factors as hubs that integrate multi-scale networks in budding yeast. Nucleic Acids Research.
- Barberis, M., & van der Zee, L. (2019). Advanced Modeling of Cellular Proliferation: Toward a Multi-scale Framework Coupling Cell Cycle to Metabolism by Integrating Logical and Constraint-Based Models. Methods in Molecular Biology.
2018
- Abudukelimu, A., Barberis, M., Redegeld, F. A., Sahin, N., & Westerhoff, H. V. (2018). Predictable Irreversible Switching Between Acute and Chronic Inflammation. Frontiers in Immunology, 9, [1596]. https://doi.org/10.3389/fimmu.2018.01596 [details]
- Barberis, M. (2018). A Mechanistic Computational Model Reveals That Plasticity of CD4+ T Cell Differentiation Is a Function of Cytokine Composition and Dosage. Frontiers in Physiology.
- Barberis, M. (2018). Simulation of Stimulation: Cytokine Dosage and Cell Cycle Crosstalk Driving Timing-Dependent T Cell Differentiation. Frontiers in Physiology.
- Barberis, M., & Mondeel, D. G. A. (2018). GEMMER: GEnome-wide tool for Multi-scale Modeling data Extraction and Representation for Saccharomyces cerevisiae. Bioinformatics.
2017
- Abudukelimu, A., Mondeel, T. D. G. A., Barberis, M., & Westerhoff, H. V. (2017). Learning to read and write in evolution: from static pseudoenzymes and pseudosignalers to dynamic gear shifters. Biochemical Society Transactions, 45(3), 635-652. https://doi.org/10.1042/BST20160281 [details]
- Barberis, M., & Verbruggen, P. (2017). Quantitative Systems Biology to decipher design principles of a dynamic cell cycle network: the "Maximum Allowable mammalian Trade-Off-Weight" (MAmTOW). Npj Systems Biology and Applications, 3, [26]. https://doi.org/10.1038/s41540-017-0028-x [details]
- Barberis, M., Todd, R. G., & van der Zee, L. (2017). Advances and challenges in logical modeling of cell cycle regulation: perspective for multi-scale, integrative yeast cell models. FEMS Yeast Research, 17(1), [fow103]. https://doi.org/10.1093/femsyr/fow103 [details]
- Linke, C., Chasapi, A., González-Novo, A., Al Sawad, I., Tognetti, S., Klipp, E., ... Barberis, M. (2017). A Clb/Cdk1-mediated regulation of Fkh2 synchronizes CLB expression in the budding yeast cell cycle. Npj Systems Biology and Applications, 3, [7]. https://doi.org/10.1038/s41540-017-0008-1 [details]
- Ostrow, A. Z., Kalhor, R., Gan, Y., Villwock, S. K., Linke, C., Barberis, M., ... Aparicio, O. M. (2017). Conserved forkhead dimerization motif controls DNA replication timing and spatial organization of chromosomes in S. cerevisiae. Proceedings of the National Academy of Sciences of the United States of America, 114(12), E2411-E2419. https://doi.org/10.1073/pnas.1612422114 [details]
- Zhang, Y., Kouril, T., Snoep, J. L., Siebers, B., Barberis, M., & Westerhoff, H. V. (2017). The Peculiar Glycolytic Pathway in Hyperthermophylic Archaea: Understanding Its Whims by Experimentation In Silico. International Journal of Molecular Sciences, 18(4), [876]. https://doi.org/10.3390/ijms18040876 [details]
2015
- Westerhoff, H. V., Nakayama, S., Mondeel, T. D. G. A., & Barberis, M. (2015). Systems Pharmacology: An opinion on how to turn the impossible into grand challenges. Drug Discovery Today. Technologies, 15, 23-31. https://doi.org/10.1016/j.ddtec.2015.06.006 [details]
2013
- Linke, C., Klipp, E., Lehrach, H., Barberis, M., & Krobitsch, S. (2013). Fkh1 and Fkh2 associate with Sir2 to control CLB2 transcription under normal and oxidative stress conditions. Frontiers in Physiology, 4, [173]. https://doi.org/10.3389/fphys.2013.00173 [details]
- Supady, A., Klipp, E., & Barberis, M. (2013). A variable fork rate affects timing of origin firing and S phase dynamics in Saccharomyces cerevisiae. Journal of Biotechnology, 168(2), 174-184. https://doi.org/10.1016/j.jbiotec.2013.06.022 [details]
2015
- Naldi, A., Monteiro, P. T., Müssel, C., the Consortium for Logical Models and Tools, Kestler, H. A., Thieffry, D., Xenarios, I., Saez-Rodriguez, J., Helikar, T., Chaouiya, C., Albert, R., Barberis, M., Calzone, L., Chasapi, A., Cokelaer, T., Crespo, I., Dorier, J., Dräger, A., Hernandez, C., ... Zañudo, J. G. T. (2015). Cooperative development of logical modelling standards and tools with CoLoMoTo. Bioinformatics, 31(7), 1154-1159. https://doi.org/10.1093/bioinformatics/btv013 [details]
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Ancillary activities
No known ancillary activities
Abudukelimu, A., Barberis, M., Redegeld, F., Sahin, N., Sharma, R. P., & Westerhoff, H. V. (2020). Complex Stability and an Irrevertible Transition Reverted by Peptide and Fibroblasts in a Dynamic Model of Innate Immunity. Frontiers in Immunology, 10, [3091].