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Publications

2021

Martins Conde, P., Pfau, T., Pires Pacheco, M. I., & Sauter, T. (2021). A dynamic multi-tissue model to study human metabolism. NPJ systems biology and applications, 7(1), 5.
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2020

Albrecht, M., Lucarelli, P., Kulms, D., & Sauter, T. (2020). Computational models of melanoma. Theoretical biology & medical modelling, 17(1), 8.
Badkas, A., De Landtsheer, S., & Sauter, T. (2020). Topological network measures for drug repositioning. Briefings in bioinformatics.
Bintener, T. J. R., Pires Pacheco, M. I., & Sauter, T. (2020, May 05). Towards the routine use of in silico screenings for drug discovery using metabolic modelling. Biochemical Society Transactions.
Gui, Y., Thomas, M. H., Garcia, P., Karout, M., Halder, R., Michelucci, A., Kollmus, H., Zhou, C., Melmed, S., Schughart, K., Balling, R., Mittelbronn, M., Nadeau, J. H., Williams, R. W., Sauter, T., Buttini, M., & Sinkkonen, L. (2020, September 23). Pituitary Tumor Transforming Gene 1 Orchestrates Gene Regulatory Variation in Mouse Ventral Midbrain During Aging. Frontiers in Genetics.
Klaus, C., Hansen, J. N., Ginolhac, A., Gérard, D., Gnanapragassam, V. S., Horstkorte, R., Rossdam, C., Buettner, F. F. R., Sauter, T., Sinkkonen, L., Neumann, H., & Linnartz-Gerlach, B. (2020). Reduced sialylation triggers homeostatic synapse and neuronal loss in middle-aged mice. Neurobiology of Aging.
Martins Conde, P., Sauter, T., & Nguyen, T.-P. (2020). An efficient machine learning-based approach for screening individuals at risk of hereditary haemochromatosis. Scientific reports, 10(1), 20613.
Muller, I., Strozyk, E., Schindler, S., Beissert, S., Oo, H. Z., Sauter, T., Lucarelli, P., Raeth, S., Hausser, A., Al Nakouzi, N., Fazli, L., Gleave, M. E., Liu, H., Simon, H.-U., Walczak, H., Green, D. R., Bartek, J., Daugaard, M., & Kulms, D. (2020). Cancer Cells Employ Nuclear Caspase-8 to Overcome the p53-Dependent G2/M Checkpoint through Cleavage of USP28. Molecular cell.
Nuzzaci, D., Cansell, C., Liénard, F., Nédélec, E., Ben Fradj, S., Castel, J., Foppen, E., Denis, R., Grouselle, D., Laderrière, A., Lemoine, A., Mathou, A., Tolle, V., Heurtaux, T., Fioramonti, X., Audinat, E., Pénicaud, L., Nahon, J.-L., Rovère, C., & Benani, A. (2020). Postprandial hyperglycemia stimulates neuroglial plasticity in hypothalamic POMC neurons after a balanced meal. Cell Reports, 30, 3067-3078.
Ohnmacht, J., May, P., Sinkkonen, L., & Krüger, R. (2020, April 04). Missing heritability in Parkinson’s disease: the emerging role of non‑coding genetic variation. Journal of Neural Transmission.
Sauter, T., & Pires Pacheco, M. I. (2020). Testing informed SIR based epidemiological model for COVID-19 in Luxembourg. Eprint/Working paper retrieved from https://www.medrxiv.org/content/10.1101/2020.07.21.20159046v1.
Shahraz, A., Wißfeld, J., Ginolhac, A., Matthews, M., Sinkkonen, L., & Neumann, H. (2020, July 28). Phagocytosis‐related NADPH oxidase 2 subunit gp91phox contributes to neurodegeneration after repeated systemic challenge with lipopolysaccharides. Glia.
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2019

Albrecht, M. (2019). Mathematical Histopathology and Systems Pharmacology of Melanoma. Unpublished doctoral thesis, University of Luxembourg, ​Belvaux, ​​Luxembourg.
Alsahafi, E., Begg, K., Amelio, I., Raulf, N., Lucarelli, P., Sauter, T., & Tavassoli, M. (2019). Clinical update on head and neck cancer: molecular biology and ongoing challenges. Cell death & disease, 10(8), 540.
Becker, J. C., Gerard, D., Ginolhac, A., Sauter, T., & Sinkkonen, L. (2019, May 02). Identification of genes under dynamic post-transcriptional regulation from time-series epigenomic data. Epigenomics.
Caberlotto, L., Nguyen, T.-P., Lauria, M., Corrado, P., Rimondini, R., Maioli, S., Cedazo-Minguez, A., Sita, G., Morroni, F., & Corsi, M. (2019). Cross-disease analysis of Alzheimer’s disease and type-2 Diabetes highlights the role of autophagy in the pathophysiology of two highly comorbid diseases. Scientific Reports, 9(1), 3965.
Cecchini, V. F., Nguyen, T.-P., Pfau, T., De Landtsheer, S., & Sauter, T. (2019). An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction. In V. F., Cecchini, An Efficient Machine Learning Method to Solve Imbalanced Data in Metabolic Disease Prediction (1st ed, pp. 5). Da Nang, Vietnam: DA NANG PUBLISHING HOUSE.
Greenhalgh, K., Ramiro Garcia, J., Heinken, Ullmann, P., Bintener, T. J. R., Pacheco, M., Baginska, J., Shah, P., Frachet Bour, A., Halder, R., Fritz, J., Sauter, T., Thiele, I., Haan, S., Letellier, E., & Wilmes, P. (2019). Integrated In Vitro and In Silico Modeling Delineates the Molecular Effects of a Synbiotic Regimen on Colorectal-Cancer-Derived Cells. Cell Reports, 27, 1621–1632.
Heirendt, L., Arreckx, S., Pfau, T., Mendoza, S. N., Richelle, A., Heinken, A. K., Haraldsdottir, H. S., Wachowiak, J., Keating, S. M., Vlasov, V., Magnusdottir, S., Ng, C. Y., Preciat, G., Zagare, A., Chan, S. H. J., Aurich, M. K., Clancy, C. M., Modamio, J., Sauls, J. T., Noronha, A., Bordbar, A., Cousins, B., El Assal, D. C., Valcarcel, L. V., Apaolaza, I., Ghaderi, S., Ahookhosh, M., Ben Guebila, M., Kostromins, A., Sompairac, N., Le, H. M., Ma, D., Sun, Y., Wang, L., Yurkovich, J. T., Oliveira, M. A. P., Vuong, P. T., El Assal, L. P., Kuperstein, I., Zinovyev, A., Hinton, H. S., Bryant, W. A., Aragon Artacho, F. J., Planes, F. J., Stalidzans, E., Maass, A., Vempala, S., Hucka, M., Saunders, M. A., Maranas, C. D., Lewis, N. E., Sauter, T., Palsson, B. O., Thiele, I., & Fleming, R. M. T. (2019). Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0. Nature protocols, 14(3), 639-702.
Nickels, S., Walter, J., Bolognin, S., Gerard, D., Jaeger, C., Qing, X., Tisserand, J., Jarazo, J., Hemmer, K., Harms, A., Halder, R., Lucarelli, P., Berger, E., Antony, P., Glaab, E., Hankemeier, T., Klein, C., Sauter, T., Sinkkonen, L., & Schwamborn, J. C. (2019). Impaired serine metabolism complements LRRK2-G2019S pathogenicity in PD patients. Parkinsonism and Related Disorders.
Pacheco, M., Bintener, T. J. R., & Sauter, T. (2019). Towards the Integration of Metabolic Network Modelling and Machine Learning for the Routine Analysis of High-Throughput Patient Data. Automated Reasoning for Systems Biology and Medicine. Springer.
Pacheco, M., Bintener, T. J. R., & Sauter, T. (2019). Towards the network-based prediction of repurposed drugs using patient-specific metabolic models. EBioMedicine.
Pacheco, M., Bintener, T. J. R., Ternes, D., Kulms, D., Haan, S., Letellier, E., & Sauter, T. (2019). Identifying and targeting cancer-specific metabolism with network-based drug target prediction. EBioMedicine, 43(May 2019), 98-106.
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2018

De Landtsheer, S., Lucarelli, P., & Sauter, T. (2018). Using Regularization to Infer Cell Line Specificity in Logical Network Models of Signaling Pathways. Frontiers in physiology, 9, 550.
Del Mistro, G., Lucarelli, P., Muller, I., De Landtsheer, S., Zinoveva, A., Hutt, M., Siegemund, M., Kontermann, R. E., Beissert, S., Sauter, T., & Kulms, D. (2018). Systemic network analysis identifies XIAP and IkappaBalpha as potential drug targets in TRAIL resistant BRAF mutated melanoma. NPJ systems biology and applications, 4, 39.
Gerard, D., Schmidt, F., Ginolhac, A., Schmitz, M., Halder, R., Ebert, P., Schulz, M., Sauter, T., & Sinkkonen, L. (2018, December 14). Temporal enhancer profiling of parallel lineages identifies AHR and GLIS1 as regulators of mesenchymal multipotency. Nucleic Acids Research.
Giang, T. T., Nguyen, T.-P., Tran, Q. V., & Tran, D. H. (2018). A Fast Multiple Kernel Learning Framework with Dimensionality Reduction. In Giang, Nguyen, Q. V., Tran, & D. H., Tran, Integrated Uncertainty in Knowledge Modelling and Decision Making. IEEE.
Gonzalez-Vallinas, M., Rodriguez-Paredes, M., Albrecht, M., Sticht, C., Stichel, D., Gutekunst, J., Pitea, A., Sass, S., Sanchez-Rivera, F. J., Bermejo, J. L., Schmitt, J., De La Torre, C., Warth, A., Theis, F., Mueller, N., Gretz, N., Muley, T., Meister, M., Tschaharganeh, D. F., Schirmacher, P., Matthaus, F., & Breuhahn, K. (2018). Epigenetically Regulated Chromosome 14q32 miRNA Cluster Induces Metastasis and Predicts Poor Prognosis in Lung Adenocarcinoma Patients. Molecular cancer research : MCR.
Linnartz-Gerlach, B., Bodea, L.-G., Klaus, C., Ginolhac, A., Halder, R., Sinkkonen, L., Walter, J., Colonna, M., & Neumann, H. (2018, December 11). TREM2 triggers microglial density and age‐related neuronal loss. Glia.
Pacheco, M., & Sauter, T. (2018). The FASTCORE Family: For the Fast Reconstruction of Compact Context-Specific Metabolic Networks Models. In M., Fondi, Metabolic Network Reconstruction and Modeling. Springer.
Pacheco, M., & Sauter, T. (2018). The FASTCORE Family: For the Fast Reconstruction of Compact Context-Specific Metabolic Networks Models. Methods in Molecular Biology (Clifton, N.J.), (1716), 101-110.
Pfau, T., Christian, N., Masakapalli, S. K., Sweetlove, L. J., Poolman, M. G., & Ebenhöh, O. (2018). The intertwined metabolism during symbiotic nitrogen fixation elucidated by metabolic modelling. Scientific Reports, 8.
Raulf, N., Lucarelli, P., Thavaraj, S., Brown, S., Vicencio, J. M., Sauter, T., & Tavassoli, M. (2018). Annexin A1 regulates EGFR activity and alters EGFR-containing tumour-derived exosomes in head and neck cancers. European journal of cancer (Oxford, England : 1990), 102, 52-68.
Rozanc, J., Sakellaropoulos, T., Antoranz, A., Gutta, C., Podder, B., Vetma, V., Rufo, N., Agostinis, P., Pliaka, V., Sauter, T., Kulms, D., Rehm, M., & Alexopoulos, L. G. (2018, October 15). Phosphoprotein patterns predict trametinib responsiveness and optimal trametinib sensitisation strategies in melanoma. Cell death and differentiation.
Seip, K., Jorgensen, K., Haselager, M. V., Albrecht, M., Haugen, M. H., Egeland, E. V., Lucarelli, P., Engebraaten, O., Sauter, T., Maelandsmo, G. M., & Prasmickaite, L. (2018). "Stroma-induced phenotypic plasticity offers phenotype-specific targeting to improve melanoma treatment". Cancer letters.
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2017

Albrecht, M., Stichel, D., Müller, B., Merkle, R., Sticht, C., Gretz, N., Klingmüller, U., Breuhahn, K., & Matthäus, F. (2017). TTCA: an R package for the identification of differentially expressed genes in time course microarray data. BMC Bioinformatics, 18(1), 33.
Bouvy-Liivrand, M.* , Hernandez de Sande, A.* , Pölönen, P., Mehtonen, J., Vuorenmaa, T., Niskanen, H., Sinkkonen, L., Kaikkonen, M., & Heinäniemi, M. (2017, July 29). Analysis of primary microRNA loci from nascent transcriptomes reveals regulatory domains governed by chromatin architecture. Nucleic Acids Research.
* These authors have contributed equally to this work.
De Landtsheer, S., Trairatphisan, P., Lucarelli, P., & Sauter, T. (2017, July). FALCON: A Toolbox for the Fast Contextualisation of Logical Networks. Bioinformatics (Oxford, England).
Giang, T. T., Nguyen, T.-P., & Tran, D. H. (2017). Stratifying cancer patients based on multiple kernel learning and dimensionality reduction. In T. T., Giang, T.-P., Nguyen, & Tran, 9th International Conference on Knowledge and Systems Engineering (KSE). IEE.
Lucarelli, P., De Landtsheer, S., & Sauter, T. (2017). Systembasierte Analyse von Wirkstoffresistenzen bei Melanom. Eprint/Working paper retrieved from https://www.systembiologie.de/lw_resource/datapool/_items/item_250/ptj-005_systembiologie_12_2017_web-150dpi_171122.pdf.
Lucarelli, P., Schilling, M., Kreutz, C., Vlasov, A., Boehm, M. E., Iwamoto, N., Steiert, B., Lattermann, S., Wasch, M., Stepath, M., Matter, M. S., Heikenwalder, M., Hoffmann, K., Deharde, D., Damm, G., Seehofer, D., Muciek, M., Gretz, N., Lehmann, W. D., Timmer, J., & Klingmuller, U. (2017, December 13). Resolving the Combinatorial Complexity of Smad Protein Complex Formation and Its Link to Gene Expression. Cell Systems.
Sobotta, S., Raue, A., Huang, X., Vanlier, J., Junger, A., Bohl, S., Albrecht, U., Hahnel, M. J., Wolf, S., Mueller, N. S., D'Alessandro, L. A., Mueller-Bohl, S., Boehm, M. E., Lucarelli, P., Bonefas, S., Damm, G., Seehofer, D., Lehmann, W. D., Rose-John, S., van der Hoeven, F., Gretz, N., Theis, F. J., Ehlting, C., Bode, J. G., Timmer, J., Schilling, M., & Klingmuller, U. (2017). Model Based Targeting of IL-6-Induced Inflammatory Responses in Cultured Primary Hepatocytes to Improve Application of the JAK Inhibitor Ruxolitinib. Frontiers in physiology, 8, 775.
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2016

Albrecht, M., Sciumè, G., Lucarelli, P., & Sauter, T. (2016). Thermodynamically constrained averaging theory for cancer growth modelling. IFAC-PapersOnLine, 49(26), 289-294.
Carboni, L., Nguyen, T.-P., & Caberlotto, L. (2016). Systems biology integration of proteomic data in rodent models of depression reveals involvement of the immune response and glutamatergic signalling. Proteomics. Clinical Applications.
Hoenen, C., Gustin, A., Birck, C., Kirchmeyer, M., Beaume, N., Felten, P., Grandbarbe, L., Heuschling, P., & Heurtaux, T. (2016, September 13). Alpha-Synuclein Proteins Promote Pro-Inflammatory Cascades in Microglia: Stronger Effects of the A53T Mutant. PLoS ONE.
Iwamoto, N., D'Alessandro, L. A., Depner, S., Hahn, B., Kramer, B. A., Lucarelli, P., Vlasov, A., Stepath, M., Bohm, M. E., Deharde, D., Damm, G., Seehofer, D., Lehmann, W. D., Klingmuller, U., & Schilling, M. (2016). Context-specific flow through the MEK/ERK module produces cell- and ligand-specific patterns of ERK single and double phosphorylation. Science signaling, 9(413), 13.
Lecca, P., Ihekawaba, A., Re, A., Mura, I., & Nguyen, T.-P. (2016). Computational Systems Biology: Inference and Modelling. Amsterdam, Netherlands: Elsevier.
Lommel, M., Trairatphisan, P., Gäbler, K., Laurini, C., Muller, A., Kaoma, T., Vallar, L., Sauter, T., & Schaffner, E. (2016). L-plastin Ser5 phosphorylation in breast cancer cells and in vitro is mediated by RSK downstream of the ERK/MAPK pathway. FASEB Journal.
Martins Conde, P., Sauter, T., & Pfau, T. (2016). Constraint based modelling going multicellular. Frontiers in Molecular Biosciences, 3(3).
Marwitz, S., Depner, S., Dvornikov, D., Merkle, R., Szczygiel, M., Muller-Decker, K., Lucarelli, P., Wasch, M., Mairbaurl, H., Rabe, K. F., Kugler, C., Vollmer, E., Reck, M., Scheufele, S., Kroger, M., Ammerpohl, O., Siebert, R., Goldmann, T., & Klingmuller, U. (2016). Downregulation of the TGF-beta pseudoreceptor BAMBI in non-small cell lung cancer enhances TGF-beta signaling and invasion. Cancer research.
Pacheco, M., Pfau, T., & Sauter, T. (2016, January 22). Benchmarking procedures for high-throughput context specific reconstruction algorithms. Frontiers in Physiology.
Trairatphisan, P., Wiesinger, M., Bahlawane, C., Haan, S., & Sauter, T. (2016). A Probabilistic Boolean Network Approach for the Analysis of Cancer-Specific Signalling: A Case Study of Deregulated PDGF Signalling in GIST. PloS one, 11(5), 0156223.
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2015

Adlakha, N.* , Pfau, T.* , Ebenhöh, O., & Yazdani, S. S. (2015). Insight into metabolic pathways of the potential biofuel producer, Paenibacillus polymyxa ICGEB2008. Biotechnology for Biofuels, 8(159).
* These authors have contributed equally to this work.
Bahlawane, C., Eulenfeld, R., Wiesinger, M., Wang, J., Muller, A., Girod, A., Nazarov, P. V., Felsch, K., Vallar, L., Sauter, T., Satagopam, V., & Haan, S. (2015). Constitutive activation of oncogenic PDGFRalpha-mutant proteins occurring in GIST patients induces receptor mislocalisation and alters PDGFRalpha signalling characteristics. Cell Communication and Signaling, 13, 21.
Birck, C., Koncina, E., Heurtaux, T., Glaab, E., Michelucci, A., Heuschling, P., & Grandbarbe, L. (2015). Transcriptomic analyses of primary astrocytes under TNFα treatment. Genomics Data, 7, 7-11.
Dorosz, S. A., Ginolhac, A., Kähne, T., Naumann, M., Sauter, T., Salsmann, A., & Bueb, J.-L. (2015). Role of Calprotectin as a Modulator of the IL27-Mediated Proinflammatory Effect on Endothelial Cells. Mediators of Inflammation, 2015, 1-16.
Gabel, S., Koncina, E., Dorban, G., Heurtaux, T., Birck, C., Glaab, E., Michelucci, A., Heuschling, P., & Grandbarbe, L. (2015). Inflammation Promotes a Conversion of Astrocytes into Neural Progenitor Cells via NF-κB Activation. Molecular Neurobiology, 53(8), 5041-5055.
Galhardo, M. S., Berninger, P., Nguyen, T.-P., Sauter, T., & Sinkkonen, L. (2015). Cell type-selective disease-association of genes under high regulatory load. Nucleic Acids Research, 43(18), 8839-8855.
Gustin, A., Kirchmeyer, M., Koncina, E., Felten, P., Losciuto, S., Heurtaux, T., Tardivel, A., Heuschling, P., & Dostert, C. (2015). NLRP3 Inflammasome Is Expressed and Functional in Mouse Brain Microglia but Not in Astrocytes. PLoS ONE, 10(6).
Haan, S., Bahlawane, C., Wang, J., Nazarov, P. V., Muller, A., Eulenfeld, R., Haan, C., Rolvering, C., Vallar, L., Satagopam, V., Sauter, T., & Wiesinger, M. (2015). The oncogenic FIP1L1-PDGFRalpha fusion protein displays skewed signaling properties compared to its wild-type PDGFRalpha counterpart. JAK-STAT, 4(1), 1062596.
Hillje, A.-L., Beckmann, E., Pavlou, M. A., Jäger, C., Pacheco, M., Sauter, T., Schwamborn, J. C., & Lewejohann, L. (2015). The neural stem cell fate determinant TRIM32 regulates complex behavioral traits. Frontiers in Cellular Neuroscience.
Jordan, F., Lauria, M., Scotti, M., Nguyen, T.-P., Praveen, P., Morine, M., & Priami, C. (2015). Diversity of key players in the microbial ecosystems of the human body. Scientific reports, 5, 15920.
Makadia, H. K., Anderson, W. D., Fey, D., Sauter, T., Schwaber, J. S., & Vadigepalli, R. (2015). Multiscale model of dynamic neuromodulation integrating neuropeptide-induced signaling pathway activity with membrane electrophysiology. Biophysical journal, 108(1), 211-23.
Nguyen, T.-P., Priami, C., & Caberlotto, L. (2015). Novel drug target identification for the treatment of dementia using multi-relational association mining. Scientific Reports, 5.
Pacheco, M., John, E.* , Kaoma, T., Heinäniemi, M., Nicot, N., Vallar, L., Bueb, J.-L., Sinkkonen, L., & Sauter, T. (2015). Integrated metabolic modelling reveals cell-type specific epigenetic control points of the macrophage metabolic network. BMC Genomics, 16(809).
* These authors have contributed equally to this work.
Pfau, T., Pacheco, M., & Sauter, T. (2015). Towards improved genome-scale metabolic network reconstructions: unification, transcript specificity and beyond. Briefings in bioinformatics.
Roume, H., Buschart, A., Muller, E., May, P., Satagopam, V., Laczny, C. C., Narayanasamy, S., Lebrun, L., Hoopmann, M., Schupp, J., Gillece, J., Hicks, N., Engelthaler, D., Sauter, T., Keim, P., Moritz, R., & Wilmes, P. (2015). Comparative integrated omics: identification of key functionalities in microbial community-wide metabolic networks. Biofilms and Microbiomes, 1(15007).
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2014

Bodea, L.-G., Wang, Y., Linnartz-Gerlach, B., Kopatz, J., Sinkkonen, L., Musgrove, R., Kaoma, T., Muller, A., Vallar, L., Di Monte, D., Balling, R., & Neumann, H. (2014). Neurodegeneration by Activation of the Microglial Complement–Phagosome Pathway. Journal of Neuroscience, 34(25), 8546-8556.
Ederer, M., Steinsiek, S., Stagge, S., Rolfe, M., Ter Beek, A., Knies, D., Teixeira de Mattos, M., Sauter, T., Green, J., Poole, R., Bettenbrock, K., & Sawodny, O. (2014). A mathematical model of metabolism and regulation provides a systems-level view of how Escherichia coli responds to oxygen. Frontiers in Microbiology, 5(124).
Galhardo, M. S., Sinkkonen, L., Berninger, P., Lin, J., Sauter, T., & Heinäniemi, M. (2014). ChIP-seq profiling of the active chromatin marker H3K4me3 and PPARγ, CEBPα and LXR target genes in human SGBS adipocytes. Genomics Data, 2, 230-236.
Galhardo, M. S., Sinkkonen, L., Berninger, P., Lin, J., Sauter, T., & Heinäniemi, M. (2014). Transcriptomics profiling of human SGBS adipogenesis. Genomics Data, 2, 246-248.
Henkel, S. G., Beek, A. T., Steinsiek, S., Stagge, S., Bettenbrock, K., de Mattos, M. J. T., Sauter, T., Sawodny, O., & Ederer, M. (2014). Basic Regulatory Principles of Escherichia coli's Electron Transport Chain for Varying Oxygen Conditions. PloS one, 9(9), 107640.
Konrath, F., Witt, J., Sauter, T., & Kulms, D. (2014). Identification of New IkappaBalpha Complexes by an Iterative Experimental and Mathematical Modeling Approach. PLoS computational biology, 10(3), 1003528.
Liivrand, M., Heinäniemi, M., John, E., Schneider, J., Sauter, T., & Sinkkonen, L. (2014). Combinatorial regulation of lipoprotein lipase by microRNAs during mouse adipogenesis. RNA Biology, 11(1), 76-91.
Trairatphisan, P., Mizera, A., Pang, J., Tantar, A.-A., & Sauter, T. (2014). optPBN: An Optimisation Toolbox for Probabilistic Boolean Networks. PLoS ONE, 9(7), 98001 (1-15.
Vlassis, N., Pacheco, M., & Sauter, T. (2014). Fast reconstruction of compact context-specific metabolic network models. PLoS Computational Biology, 10(1), 1003424.
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2013

Baumuratova, T., Dobre, S., Bastogne, T., & Sauter, T. (2013). Switch of Sensitivity Dynamics Revealed with DyGloSA Toolbox for Dynamical Global Sensitivity Analysis as an Early Warning for System's Critical Transition. PloS one, 8(12), 82973.
Blanchard, B., Heurtaux, T., & Nait Oumesmar, B. (2013). Tocopherol derivative TFA-12 promotes myelin repair in experimental models of multiple sclerosis. Journal of Neuroscience, 33(28), 11633-42.
Galhardo, M. S.* , Sinkkonen, L.* , Berninger, P., Lin, J., Sauter, T., & Heinäniemi, M. (2013, November 05). Integrated analysis of transcript-level regulation of metabolism reveals disease-relevant nodes of the human metabolic network. Nucleic Acids Research.
* These authors have contributed equally to this work.
Heinäniemi, M., Nykter, M., Kramer, R., Wienecke, A., Sinkkonen, L., Zhou, J. X., Kreisberg, R., Kauffman, S. A., Huang, S., & Shmulevich, I. (2013, April 21). Gene-pair expression signatures reveal lineage control. Nature Methods.
Mizera, A., Pang, J., Sauter, T., & Trairatphisan, P. (2013). A balancing act: Parameter estimation for biological models with steady-state measurements. Proceedings of 11th Conference on Computational Methods in Systems Biology (CMSB'13) (pp. 253-254). Springer.
Mizera, A., Pang, J., Sauter, T., & Trairatphisan, P. (2013). Mathematical modelling of the Platelet-Derived Growth Factor (PDGF) signalling pathway. Proceedings of 4th Workshop on Computational Models for Cell Processes (CompMod'13) (pp. 35).
Pfau, T. (2013). Modelling Metabolic Interactions in the Legume-Rhizobia Symbiosis. Unpublished doctoral thesis, University of Aberdeen, ​Aberdeen, ​​United Kingdom.
Shi, L., Jong, L., Wittig, U., Lucarelli, P., Stepath, M., Mueller, S., D'Alessandro, L. A., Klingmuller, U., & Muller, W. (2013). Excemplify: a flexible template based solution, parsing and managing data in spreadsheets for experimentalists. Journal of integrative bioinformatics, 10(2), 220.
Trairatphisan, P., Mizera, A., Pang, J., Tantar, A.-A., Schneider, J., & Sauter, T. (2013). Recent development and biomedical applications of probabilistic Boolean networks. Cell Communication and Signaling, 11(46).
Vlassis, N., Pacheco, M., & Sauter, T. (2013). Fast reconstruction of compact context-specific metabolic network models. Eprint/Working paper retrieved from http://arxiv.org/abs/1304.7992.
Vlassis, N., Pacheco, M., & Sauter, T. (2013). Fastcore: An algorithm for fast reconstruction of context-specific metabolic network models. Proc. 8th BeNeLux Bioinformatics Conference.
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2012

John, E., Wienecke-Baldacchino, A., Liivrand, M., Heinäniemi, M., Carlberg, C., & Sinkkonen, L. (2012). Dataset integration identifies transcriptional regulation of microRNA genes by PPARgamma in differentiating mouse 3T3-L1 adipocytes. Nucleic Acids Research, 40(10), 4446-4460.
Losciuto, S., Dorban, G., Gabel, S., Gustin, A., Hoenen, C., Grandbarbe, L., Heuschling, P., & Heurtaux, T. (2012). An efficient method to limit microglia-dependent effects in astroglial cultures. Journal of Neuroscience Methods, 207(1), 59-71.
Rolfe, M., Ocone, A., Stapleton, M., Hall, S., Trotter, E., Poole, R., Sanguinetti, G., Green, J., SysMO-SUMO consortium, & Sauter, T. (Other coll.). (2012). Systems analysis of transcription factor activities in environments with stable and dynamic oxygen concentrations. Open Biology, 2(7), 120091.
Wegner, K., Bachmann, A., Schad, J.-U., Lucarelli, P., Sahle, S., Nickel, P., Meyer, C., Klingmuller, U., Dooley, S., & Kummer, U. (2012). Dynamics and feedback loops in the transforming growth factor beta signaling pathway. Biophysical chemistry, 162, 22-34.
Witt, J., Konrath, F., Sawodny, O., Ederer, M., Kulms, D., & Sauter, T. (2012). Analysing the role of UVB-induced translational inhibition and PP2Ac deactivation in NF-kappaB signalling using a minimal mathematical model. PLoS ONE, 7(7), 40274.
Yuan, Q., Trairatphisan, P., Pang, J., Mauw, S., Wiesinger, M., & Sauter, T. (2012). Probabilistic model checking of the PDGF signaling pathway. Transactions on Computational Systems Biology, XIV, 151-180.
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2011

Guziolowski, C., Blachon, S., Baumuratova, T., Stoll, G., Radulescu, O., & Siegel, A. (2011). Designing logical rules to model the response of biomolecular networks with complex interactions: an application to cancer modeling. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 8(5), 1223-34.
Henkel, S., Nagele, T., Hormiller, I., Sauter, T., Sawodny, O., Ederer, M., & Heyer, A. G. (2011). A systems biology approach to analyse leaf carbohydrate metabolism in Arabidopsis thaliana. EURASIP Journal on Bioinformatics & Systems Biology, 2011(1), 2.
Witt, J., Barisic, S., Sawodny, O., Ederer, M., Kulms, D., & Sauter, T. (2011). Modeling time delay in the NFkappaB signaling pathway following low dose IL-1 stimulation. EURASIP Journal on Bioinformatics & Systems Biology, 2011(1), 3.
Yuan, Q., Pang, J., Mauw, S., Trairatphisan, P., Wiesinger, M., & Sauter, T. (2011). A study of the PDGF signaling pathway with PRISM. Proceedings of the 3rd Workshop on Computational Models for Cell Processes, EPTCS 67, 65-81.
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2010

Baumuratova, T., Surdez, D., Delyon, B., Stoll, G., Delattre, O., Radulescu, O., & Siegel, A. (2010). Localizing potentially active post-transcriptional regulations in the Ewing's sarcoma gene regulatory network. BMC Systems Biology, 4, 146.
Heurtaux, T., Michelucci, A., Losciuto, S., Gallotti, C., Felten, P., Dorban, G., Grandbarbe, L., Morga, E., & Heuschling, P. (2010). Microglial activation depends on beta-amyloid conformation: role of the formylpeptide receptor 2. Journal of Neurochemistry, 114(2), 576-586.
Lahnalampi, M., Heinäniemi, M., Sinkkonen, L., Wabitsch, M., & Carlberg, C. (2010). Time-Resolved Expression Profiling of the Nuclear Receptor Superfamily in Human Adipogenesis. PLoS ONE, 5(9).
Nagele, T., Henkel, S., Hormiller, I., Sauter, T., Sawodny, O., Ederer, M., & Heyer, A. G. (2010). Mathematical modeling of the central carbohydrate metabolism in Arabidopsis reveals a substantial regulatory influence of vacuolar invertase on whole plant carbon metabolism. Plant Physiology, 153(1), 260-72.
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2009

Michelucci, A., Heurtaux, T., Grandbarbe, L., Morga, E., & Heuschling, P. (2009). Characterization of the microglial phenotype under specific pro-inflammatory and anti-inflammatory conditions: Effects of oligomeric and fibrillar amyloid-beta. Journal of Neuroimmunology, 210(1-2), 3-12.
Schlatter, R., Conzelmann, H., Gilles, E. D., Sawodny, O., & Sauter, T. (2009). Analysis of an apoptotic core model focused on experimental design using artificial data. IET Systems Biology, 3(4), 255-65.
Schlatter, R., Schmich, K., Avalos Vizcarra, I., Scheurich, P., Sauter, T., Borner, C., Ederer, M., Merfort, I., & Sawodny, O. (2009). ON/OFF and beyond--a boolean model of apoptosis. PLoS Computational Biology, 5(12), 1000595.
Witt, J., Barisic, S., Schumann, E., Allgower, F., Sawodny, O., Sauter, T., & Kulms, D. (2009). Mechanism of PP2A-mediated IKK beta dephosphorylation: a systems biological approach. BMC Systems Biology, 3, 71.
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2008

Feuer, R., Ederer, M., Gilles, E. D., Sprenger, G., Sawodny, O., & Sauter, T. (2008). Analyse der evolutiven Adaptation am Beispiel einer pyruvat-auxotrophen Escherichia coli-Mutante. Automatisierungstechnik, 56, 257-268.
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2007

Bettenbrock, K., Sauter, T., Jahreis, K., Kremling, A., Lengeler, J. W., & Gilles, E.-D. (2007). Correlation between growth rates, EIIACrr phosphorylation, and intracellular cyclic AMP levels in Escherichia coli K-12. Journal of Bacteriology, 189(19), 6891-900.
Feuer, R., Ederer, M., Trachtmann, N., Sauter, T., Gilles, E. D., Sprenger, G., & Sawodny, O. (2007). Methods for analysis of evolutive adaptation of E. coli. Proceedings of the SICE Annual Conference, September 17-20, 2007 Kagawa University, Takamatsu City, Japan.
Grandbarbe, L., Michelucci, A., Heurtaux, T., Hemmer, K., Morga, E., & Heuschling, P. (2007). Notch signaling modulates the activation of microglial cells. Glia, 55(15), 1519-30.
Witt, J., Husser, S., Kulms, D., Barisic, S., Sawodny, O., & Sauter, T. (2007). Modeling and Analysis of UVB Influence on IL-1 induced NF-kappaB Signaling. Proceedings of the FOSBE, September 9-12, Stuttgart, Germany.
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2006

Bettenbrock, K., Fischer, S., Kremling, A., Jahreis, K., Sauter, T., & Gilles, E.-D. (2006). A quantitative approach to catabolite repression in Escherichia coli. Journal of Biological Chemistry, 281(5), 2578-84.
Conzelmann, H., Saez-Rodriguez, J., Sauter, T., Kholodenko, B. N., & Gilles, E. D. (2006). A domain-oriented approach to the reduction of combinatorial complexity in signal transduction networks. BMC Bioinformatics, 7, 34.
Eissing, T., Bullinger, E., Waldherr, S., Gondro, C., Sawodny, O., Allgöwer, F., Scheurich, P., & Sauter, T. (2006). Sensitivity analysis of programmed cell death and implications for crosstalk phenomena during Tumor Necrosis Factor stimulation. Proceedings of IEEE International Conference on Control Applications (CCA), October 4-6, 2006, Technische Universität München, Germany.
Hao, H., Zak, D. E., Sauter, T., Schwaber, J., & Ogunnaike, B. A. (2006). Modeling the VPAC2-activated cAMP/PKA signaling pathway: from receptor to circadian clock gene induction. Biophysical Journal, 90(5), 1560-71.
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2004

Conzelmann, H., Saez-Rodriguez, J., Sauter, T., Bullinger, E., Allgower, F., & Gilles, E. D. (2004). Reduction of mathematical models of signal transduction networks: simulation-based approach applied to EGF receptor signalling. Systems biology, 1(1), 159-69.
Kremling, A., Bettenbrock, K., Fischer, S., Ginkel, M., Sauter, T., & Gilles, E. D. (2004). Towards whole cell "in silico" models for cellular systems: model set-up and model validation. Lecture Notes in Control and Information Sciences: Proceedings of the first multidisciplinary international symposium on Positive Systems (pp. 95-102). Springer.
Kremling, A., Fischer, S., Sauter, T., Bettenbrock, K., & Gilles, E. D. (2004). Time hierarchies in the Escherichia coli carbohydrate uptake and metabolism. Bio Systems, 73(1), 57-71.
Kremling, A., Fischer, S., Gadkar, K., Doyle, F. J., Sauter, T., Bullinger, E., Allgower, F., & Gilles, E. D. (2004). A benchmark for methods in reverse engineering and model discrimination: problem formulation and solutions. Genome Research, 14(9), 1773-85.
Sauter, T., & Bullinger, E. (2004). Detailed Mathematical Modeling of Metabolic and Regulatory Networks. BIOforum Europe, 02, 62-64.
Sauter, T., & Gilles, E. D. (2004). Modeling and experimental validation of the signal transduction via the Escherichia coli sucrose phospho transferase system. Journal of Biotechnology, 110(2), 181-99.
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2003

Ederer, M., Sauter, T., Bullinger, E., Gilles, E. D., & Allgöwer, F. (2003). An approach for dividing models of biological reaction networks into functional units. Simulation, 79, 703-716.
Sauter, T. (2003). Die bakterielle Signalverarbeitung am Beispiel des Sucrose Phosphotransferasesystems in Escherichia coli : Modellierung und experimentelle Überprüfung. Unpublished doctoral thesis, Universität Stuttgart, ​​Germany.
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2001

Kremling, A., Sauter, T., Bullinger, E., Ederer, M., Allgöwer, F., & Gilles, E. D. (2001). Biosystems Engineering: Applying methods from systems theory to biological systems. Proceedings of the 2nd International Conference on Systems Biology 4.-7.11.2001, Pasadena.
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