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Research GBB Molecular Systems Biology



Zylstra, A., & Heinemann, M. (2022). Metabolic dynamics during the cell cycle. Current Opinion in Systems Biology, 30, [100415].
Van den Bergh, B., Schramke, H., Michiels, J. E., Kimkes, T. E. P., Radzikowski, J. L., Schimpf, J., Vedelaar, S. R., Burschel, S., Dewachter, L., Lončar, N., Schmidt, A., Meijer, T., Fauvart, M., Friedrich, T., Michiels, J., & Heinemann, M. (2022). Mutations in respiratory complex I promote antibiotic persistence through alterations in intracellular acidity and protein synthesis. Nature Communications, 13(1), [546].
Losa, J., Leupold, S., Alonso-Martinez, D., Vainikka, P., Thallmair, S., Tych, K. M., Marrink, S. J., & Heinemann, M. (2022). Perspective: A stirring role for metabolism in cells. Molecular Systems Biology, 18(4), [e10822].
Litsios, A., Goswami, P., Terpstra, H. M., Coffin, C., Vuillemenot, L-A., Rovetta, M., Ghazal, G., Guerra, P., Buczak, K., Schmidt, A., Tollis, S., Tyers, M., Royer, C. A., Milias-Argeitis, A., & Heinemann, M. (2022). The timing of Start is determined primarily by increased synthesis of the Cln3 activator rather than dilution of the Whi5 inhibitor. Molecular Biology of the Cell, 33(5), [rp2].
Novarina, D., Koutsoumpa, A., & Milias-Argeitis, A. (2022). A user-friendly and streamlined protocol for CRISPR/Cas9 genome editing in budding yeast. STAR protocols, 3(2), [101358].


Sellner, B., Prakapaitė, R., van Berkum, M., Heinemann, M., Harms, A., & Jenal, U. (2021). A New Sugar for an Old Phage: a c-di-GMP-Dependent Polysaccharide Pathway Sensitizes Escherichia coli for Bacteriophage Infection. Mbio, 12(6), [e03246-21].
Vedelaar, S. R., Radzikowski, J. L., & Heinemann, M. (2021). A Robust Method for Generating, Quantifying, and Testing Large Numbers of Escherichia coli Persisters. Methods in molecular biology (Clifton, N.J.), 2357, 41-62.
Ortega, A. D., Takhaveev, V., Vedelaar, S. R., Long, Y., Mestre-Farràs, N., Incarnato, D., Ersoy, F., Olsen, L. F., Mayer, G., & Heinemann, M. (2021). A synthetic RNA-based biosensor for fructose-1,6-bisphosphate that reports glycolytic flux. Cell Chemical Biology, 28(11), 1554-1568.e8. [j.chembiol.2021.04.006].
Alseekh, S., Aharoni, A., Brotman, Y., Contrepois, K., D'Auria, J., Ewald, J., C Ewald, J., Fraser, P. D., Giavalisco, P., Hall, R. D., Heinemann, M., Link, H., Luo, J., Neumann, S., Nielsen, J., Perez de Souza, L., Saito, K., Sauer, U., Schroeder, F. C., ... Fernie, A. R. (2021). Mass spectrometry-based metabolomics: A guide for annotation, quantification and best reporting practices. Nature Methods, 18(7), 747-756.
Yang, X., Heinemann, M., Howard, J., Huber, G., Iyer-Biswas, S., Le Treut, G., Lynch, M., Montooth, K. L., Needleman, D. J., Pigolotti, S., Rodenfels, J., Ronceray, P., Shankar, S., Tavassoly, I., Thutupalli, S., Titov, D. V., Wang, J., & Foster, P. J. (2021). Physical bioenergetics: Energy fluxes, budgets, and constraints in cells. Proceedings of the National Academy of Sciences of the United States of America, 118(26), [e2026786118].
Kruitbosch, H., Mzayek, Y., Omlor, S., Guerra, P., & Milias-Argeitis, A. (2022). A convolutional neural network for segmentation of yeast cells without manual training annotations. Bioinformatics (Oxford, England), 38(5), 1427-1433. [btab835].
Guerra, P., Vuillemenot, L-A., Rae, B., Ladyhina, V., & Milias-Argeitis, A. (2022). Systematic In Vivo Characterization of Fluorescent Protein Maturation in Budding Yeast. ACS Synthetic Biology, 11(3), 1129-1141. [acssynbio.1c00387].
Kurdyaeva, T., & Milias Argeitis, A. (2021). Moment-based uncertainty propagation for deterministic biochemical network models with rational reaction rates. In Proceedings of the European Control Conference 2021 EUCA.
Kurdyaeva, T., & Milias-Argeitis, A. (2021). Uncertainty propagation for deterministic models of biochemical networks using moment equations and the extended Kalman filter. Journal of the Royal Society Interface, 18(181), [20210331].
Novarina, D., Guerra, P., & Milias-Argeitis, A. (2021). Vacuolar Localization via the N-terminal Domain of Sch9 is Required for TORC1-dependent Phosphorylation and Downstream Signal Transduction. Journal of Molecular Biology, 433(24), [167326].
Kamenz, J., Qiao, R., Yang, Q., & Ferrell, J. E. (2021). Real-Time Monitoring of APC /C-Mediated Substrate Degradation Using Xenopus laevis Egg Extracts. In Methods in Molecular Biology (pp. 29-38). (Methods in Molecular Biology; Vol. 2329). Humana Press.


Heinemann, M., Basan, M., & Sauer, U. (2020). Implications of initial physiological conditions for bacterial adaptation to changing environments. Molecular Systems Biology, 16(9), e9965. [e9965].
Milias Argeitis, A., & Kurdyaeva, T. (2020). Derivation of moment equations for a nonlinear gene expression model with initial condition and parameter uncertainty.
Kamenz, J., Gelens, L., & Ferrell, J. E. (2021). Bistable, Biphasic Regulation of PP2A-B55 Accounts for the Dynamics of Mitotic Substrate Phosphorylation. Current Biology, 31(4), 794-808.
Lockhead, S., Moskaleva, A., Kamenz, J., Chen, Y., Kang, M., Reddy, A. R., Santos, S. D. M., & Ferrell, J. E. (2020). The Apparent Requirement for Protein Synthesis during G2 Phase Is due to Checkpoint Activation. Cell reports, 32(2), [107901].


Kimkes, T. E. P., & Heinemann, M. (2020). How bacteria recognise and respond to surface contact. FEMS Microbiology Reviews, 44(1), 106-122.
Niebel, B., Leupold, S., & Heinemann, M. (2019). An upper limit on Gibbs energy dissipation governs cellular metabolism. Nature Metabolism, 1, 125-131.
Balaban, N. Q., Helaine, S., Lewis, K., Ackermann, M., Aldridge, B., Andersson, D. I., Brynildsen, M. P., Bumann, D., Camilli, A., Collins, J. J., Dehio, C., Fortune, S., Ghigo, J-M., Hardt, W-D., Harms, A., Heinemann, M., Hung, D. T., Jenal, U., Levin, B. R., ... Zinkernagel, A. (2019). Definitions and guidelines for research on antibiotic persistence. Nature Reviews Microbiology, 17(7), 441-448.
Litsios, A., Huberts, D. H. E. W., Terpstra, H. M., Guerra, P., Schmidt, A., Buczak, K., Papagiannakis, A., Rovetta, M., Hekelaar, J., Hubmann, G., Exterkate, M., Milias-Argeitis, A., & Heinemann, M. (2019). Differential scaling between G1 protein production and cell size dynamics promotes commitment to the cell division cycle in budding yeast. Nature Cell Biology, 21(11), 1382-1392.
Ozsezen, S., Papagiannakis, A., Chen, H., Niebel, B., Milias-Argeitis, A., & Heinemann, M. (2019). Inference of the High-Level Interaction Topology between the Metabolic and Cell-Cycle Oscillators from Single-Cell Dynamics. Cell systems, 9(4), 354-365.
Zhang, Z., Kimkes, T. E. P., & Heinemann, M. (2019). Manipulating rod-shaped bacteria with optical tweezers. Scientific Reports, 9(1), [19086].
Monteiro, F., Hubmann, G., Takhaveev, V., Vedelaar, S. R., Norder, J., Hekelaar, J., Saldida, J., Litsios, A., Wijma, H. J., Schmidt, A., & Heinemann, M. (2019). Measuring glycolytic flux in single yeast cells with an orthogonal synthetic biosensor. Molecular Systems Biology, 15(12), [e9071].
Balaban, N. Q., Helaine, S., Lewis, K., Ackermann, M., Aldridge, B., Andersson, D. I., Brynildsen, M. P., Bumann, D., Camilli, A., Collins, J. J., Dehio, C., Fortune, S., Ghigo, J-M., Hardt, W-D., Harms, A., Heinemann, M., Hung, D. T., Jenal, U., Levin, B. R., ... Zinkernagel, A. (2019). Publisher Correction: Definitions and guidelines for research on antibiotic persistence. Nature Reviews Microbiology, 17(7), 460-460.
Leupold, S., Hubmann, G., Litsios, A., Meinema, A. C., Takhaveev, V., Papagiannakis, A., Niebel, B., Janssens, G., Siegel, D., & Heinemann, M. (2019). Saccharomyces cerevisiae goes through distinct metabolic phases during its replicative lifespan. eLife, 8, [e41046].
Yang, Y-S., Kato, M., Wu, X., Litsios, A., Sutter, B. M., Wang, Y., Hsu, C-H., Wood, N. E., Lemoff, A., Mirzaei, H., Heinemann, M., & Tu, B. P. (2019). Yeast Ataxin-2 Forms an Intracellular Condensate Required for the Inhibition of TORC1 Signaling during Respiratory Growth. Cell, 177(3), 697-710.
Kurdyaeva, T., & Milias-Argeitis, A. (2019). Efficient global sensitivity analysis of biochemical networks using Gaussian process regression. In 2018 IEEE Conference on Decision and Control, CDC 2018 (pp. 2673-2678). [8618902] (Proceedings of the IEEE Conference on Decision and Control). Institute of Electrical and Electronics Engineers Inc..


von Borzyskowski, L. S., Carrillo, M., Leupold, S., Glatter, T., Kiefer, P., Weishaupt, R., Heinemann, M., & Erb, T. J. (2018). An engineered Calvin-Benson-Bassham cycle for carbon dioxide fixation in Methylobacterium extorquens AM1. Metabolic Engineering, 47, 423-433.
Bley Folly, B., Ortega, A. D., Hubmann, G., Bonsing-Vedelaar, S., Wijma, H. J., van der Meulen, P., Milias-Argeitis, A., & Heinemann, M. (2018). Assessment of the interaction between the flux-signaling metabolite fructose-1,6-bisphosphate and the bacterial transcription factors CggR and Cra. Molecular Microbiology, 109(3), 278-290.
Zhang, Z., Milias-Argeitis, A., & Heinemann, M. (2018). Dynamic single-cell NAD(P)H measurement reveals oscillatory metabolism throughout the E. coli cell division cycle. Scientific Reports, 8(1), [2162].
Takhaveev, V., & Heinemann, M. (2018). Metabolic heterogeneity in clonal microbial populations. Current Opinion in Microbiology, 45, 30-38.
Kimkes, T. E. P., & Heinemann, M. (2018). Reassessing the role of the Escherichia coli CpxAR system in sensing surface contact. PLoS ONE, 13(11), [e0207181].
Rullan, M., Benzinger, D., Schmidt, G. W., Milias-Argeitis, A., & Khammash, M. (2018). An Optogenetic Platform for Real-Time, Single-Cell Interrogation of Stochastic Transcriptional Regulation. Molecular Cell, 70(4), 745-756.e6.
Milias Argeitis, A., & Kurdyaeva, T. (2018). Analytical calculation of Sobol sensitivity indices for Gaussian Processes with a squared exponential covariance function.
Garcia, H. G., Benzinger, D., Rullan, M., Milias-Argeitis, A., Khammash, M., Deutschbauer, A. M., Langdon, E. M., & Gladfelter, A. S. (2018). Principles of Systems Biology, No. 30. Cell systems, 7(1), 1-2.
Thadani, R., Kamenz, J., Heeger, S., Munoz, S., & Uhlmann, F. (2018). Cell-Cycle Regulation of Dynamic ChromosomeAssociation of the Condensin Complex. Cell reports, 23(8), 2308-2317.


Litsios, A., Ortega, Á. D., Wit, E. C., & Heinemann, M. (2018). Metabolic-flux dependent regulation of microbial physiology. Current Opinion in Microbiology, 42, 71-78.
Papagiannakis, A., Niebel, B., Wit, E., & Heinemann, M. (2017). A CDK-independent metabolic oscillator orchestrates the budding yeast cell cycle. Febs Journal, 284(S1), 54. [S.5.4-002].
Radzikowski, J. L., Schramke, H., & Heinemann, M. (2017). Bacterial persistence from a system-level perspective. Current Opinion in Biotechnology, 46, 98-105.
Heinemann, M., & Pilpel, Y. (2017). Editorial overview: Systems biology for biotechnology. Current Opinion in Biotechnology, 46, iv-v.
Papagiannakis, A., de Jonge, J. J., Zhang, Z., & Heinemann, M. (2017). Quantitative characterization of the auxin-inducible degron: a guide for dynamic protein depletion in single yeast cells. Scientific Reports, 7, [4704].
Filer, D., Thompson, M. A., Takhaveev, V., Dobson, A. J., Kotronaki, I., Green, J. W. M., Heinemann, M., Tullet, J. M. A., & Alic, N. (2017). RNA polymerase III limits longevity downstream of TORC1. Nature, 552(7684), 263-267.
Gupta, A., Milias-Argeitis, A., & Khammash, M. (2017). Dynamic disorder in simple enzymatic reactions induces stochastic amplification of substrate. Journal of the Royal Society Interface, 14(132), [20170311].
Kuzmanovska, I., Milias Argeitis, A., Mikelson, J., Zechner, C., & Khammash, M. (2017). Parameter inference for stochastic single-cell dynamics from lineage tree data. BMC Systems Biology, 11(52), [52].
Kamenz, J., & Ferrell, J. E. (2017). The Temporal Ordering of Cell-Cycle Phosphorylation. Molecular Cell, 65(3), 371-373.
Kamenz, J., & Hauf, S. (2017). Time To Split Up: Dynamics of Chromosome Separation. Trends in Cell Biology, 27(1), 42-54.


Papagiannakis, A., Niebel, B., Wit, E. C., & Heinemann, M. (2017). Autonomous Metabolic Oscillations Robustly Gate the Early and Late Cell Cycle. Molecular Cell, 65(2), 285-295.
Radzikowski, J. L., Vedelaar, S., Siegel, D., Ortega, Á. D., Schmidt, A., & Heinemann, M. (2016). Bacterial persistence is an active σS stress response to metabolic flux limitation. Molecular Systems Biology, 12(9), 1-18. [882].
van Rijsewijk, B. R. B. H., Kochanowski, K., Heinemann, M., & Sauer, U. (2016). Distinct transcriptional regulation of the two Escherichia coli transhydrogenases PntAB and UdhA. Microbiology-Reading, 162(9), 1672-1679.
Heinemann, M. (2016). Flux Controls Flux – a Key Challenge for Metabolic Engineering. Chemie-Ingenieur-Technik, 88(9), 1392.
Milias-Argeitis, A., & Khammash, M. (2016). Adaptive Model Predictive Control of an optogenetic system. In 2015 54th IEEE Conference on Decision and Control, CDC 2015 (Vol. 2016-February, pp. 1265-1270). [7402385] Institute of Electrical and Electronics Engineers Inc..
Milias-Argeitis, A., Rullan, M., Aoki, S. K., Buchmann, P., & Khammash, M. (2016). Automated optogenetic feedback control for precise and robust regulation of gene expression and cell growth. Nature Communications, 7, [12546].
Milias-Argeitis, A., Oliveira, A. P., Gerosa, L., Falter, L., Sauer, U., & Lygeros, J. (2016). Elucidation of Genetic Interactions in the Yeast GATA-Factor Network Using Bayesian Model Selection. PLoS Computational Biology, 12(3), 1-27. [e1004784].


Schmidt, A., Kochanowski, K., Vedelaar, S., Ahrné, E., Volkmer, B., Callipo, L., Knoops, K., Bauer, M., Aebersold, R., & Heinemann, M. (2016). The quantitative and condition-dependent Escherichia coli proteome. Nature Biotechnology, 34(1), 104-110.
Janssens, G. E., Meinema, A. C., Gonzalez, J., Wolters, J. C., Schmidt, A., Guryev, V., Bischoff, R., Wit, E. C., Veenhoff, L. M., & Heinemann, M. (2015). Protein biogenesis machinery is a driver of replicative aging in yeast. eLife, 4, [e08527].
Ruess, J., Parise, F., Milias-Argeitis, A., Khammash, M., & Lygeros, J. (2015). Iterative experiment design guides the characterization of a light-inducible gene expression circuit. Proceedings of the National Academy of Sciences, 112(26), 8148-8153.
Milias-Argeitis, A., & Khammash, M. (2015). Optimization-based Lyapunov function construction for continuous-time Markov chains with affine transition rates. In Proceedings of the IEEE Conference on Decision and Control (pp. 4617-4622). (Proceedings of the IEEE Conference on Decision and Control; Vol. 2015-February). Institute of Electrical and Electronics Engineers Inc..
Milias-Argeitis, A., Engblom, S., Bauer, P., & Khammash, M. (2015). Stochastic focusing coupled with negative feedback enables robust regulation in biochemical reaction networks. Journal of the Royal Society Interface, 12, 1-32.
Kamenz, J., Mihaljev, T., Kubis, A., Legewie, S., & Hauf, S. (2015). Robust Ordering of Anaphase Events by AdaptiveThresholds and Competing Degradation Pathways. Molecular Cell, 60, 446-459.


Daszczuk, A., Dessalegne, Y., Drenth, I., Hendriks, E., Jo, E., van Lente, T., Oldebesten, A., Parrish, J., Poljakova, W., Purwanto, A. A., van Raaphorst, R., Boonstra, M., van Heel, A., Herber, M., van der Meulen, S., Siebring, J., Sorg, R. A., Heinemann, M., Kuipers, O. P., & Veening, J-W. (2014). Bacillus subtilis Biosensor Engineered To Assess Meat Spoilage. ACS Synthetic Biology, 3(12), 999-1002.
Huberts, D. H. E. W., Gonzalez Hernandez, J., Lee, S. S., Litsios, A., Hubmann, G., Wit, E. C., & Heinemann, M. (2014). Calorie restriction does not elicit a robust extension of replicative lifespan in Saccharomyces cerevisiae. Proceedings of the National Academy of Science of the United States of America, 111(32), 11727-11731.
Kotte, O., Volkmer, B., Radzikowski, J. L., & Heinemann, M. (2014). Phenotypic bistability in Escherichia coli's central carbon metabolism. Molecular Systems Biology, 10(7), [736].
Lee, S. S., Dechant, R., Vizcarra, I. A., Huberts, D. H. E. W., Lee, L. P., Heinemann, M., & Peter, M. (2014). Single cell analysis of yeast aging using microfluidic dissection. In 18th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2014 (pp. 666-668). Chemical and Biological Microsystems Society .
Milias-Argeitis, A., Lygeros, J., & Khammash, M. (2014). Fast variance reduction for steady-state simulation and sensitivity analysis of stochastic chemical systems using shadow function estimators. Journal of Chemical Physics, 141(2), [024104].
Fromm, S. A., Kamenz, J., Nöldeke, E. R., Neu, A., Zocher, G., & Sprangers, R. (2014). In vitro reconstitution of a cellular phase-transition process that involves the mRNA decapping machinery. Angewandte Chemie - International Edition, 53(28), 7354-7359.
Kamenz, J., & Hauf, S. (2014). Slow checkpoint activation kinetics as a safety device in anaphase. Current Biology, 24(6), 646-651.


Huberts, D. H. E. W., Sik Lee, S., Gonzáles, J., Janssens, G. E., Vizcarra, I. A., & Heinemann, M. (2013). Construction and use of a microfluidic dissection platform for long-term imaging of cellular processes in budding yeast. Nature protocols, 8(6), 1019-1027.
Huberts, D. H. E. W., Janssens, G. E., Lee, S. S., Vizcarra, I. A., & Heinemann, M. (2013). Continuous High-resolution Microscopic Observation of Replicative Aging in Budding Yeast. Journal of visualized experiments : JoVE, (78), [50143].
Gerosa, L., Kochanowski, K., Heinemann, M., & Sauer, U. (2013). Dissecting specific and global transcriptional regulation of bacterial gene expression. Molecular Systems Biology, 9, [658].
Kochanowski, K., Volkmer, B., Gerosa, L., Haverkorn van Rijsewijk, B. R., Schmidt, A., & Heinemann, M. (2013). Functioning of a metabolic flux sensor in Escherichia coli. Proceedings of the National Academy of Sciences of the United States of America, 110(3), 1130-1135.
Ibáñez, A. J., Fagerer, S. R., Schmidt, A. M., Urban, P. L., Jefimovs, K., Geiger, P., Dechant, R., Heinemann, M., & Zenobi, R. (2013). Mass spectrometry-based metabolomics of single yeast cells. Proceedings of the National Academy of Sciences of the United States of America, 110(22), 8790-8794.
Zampar, G. G., Kümmel, A., Ewald, J., Jol, S., Niebel, B., Picotti, P., Aebersold, R., Sauer, U., Zamboni, N., & Heinemann, M. (2013). Temporal system-level organization of the switch from glycolytic to gluconeogenic operation in yeast. Molecular Systems Biology, 9, 651-1-651-13. [651].
Esfahani, P. M., Milias-Argeitis, A., & Chatterjee, D. (2013). Analysis of controlled biological switches via stochastic motion planning. In 2013 European Control Conference, ECC 2013 (pp. 93-98). [6669626]
Ruess, J., Milias-Argeitis, A., & Lygeros, J. (2013). Designing experiments to understand the variability in biochemical reaction networks. Journal of the Royal Society Interface, 10(88), [20130588].
Milias-Argeitis, A., & Lygeros, J. (2013). Steady-state simulation of metastable stochastic chemical systems. Journal of Chemical Physics, 138(18), [184109].
Heinrich, S., Geissen, E-M., Kamenz, J., Trautmann, S., Widmer, C., Drewe, P., Knop, M., Radde, N., Hasenauer, J., & Hauf, S. (2013). Determinants of robustness in spindle assembly checkpoint signalling. Nature Cell Biology, 15, 1328-1339.


Huberts, D. H. E. W., Niebel, B., & Heinemann, M. (2012). A flux-sensing mechanism could regulate the switch between respiration and fermentation. Fems Yeast Research, 12(2), 118-128.
Schuetz, R., Zamboni, N., Zampieri, M., Heinemann, M., & Sauer, U. (2012). Multidimensional optimality of microbial metabolism. Science, 336(6081), 601-604.
Adadi, R., Volkmer, B., Milo, R., Heinemann, M., & Shlomi, T. (2012). Prediction of Microbial Growth Rate versus Biomass Yield by a Metabolic Network with Kinetic Parameters. PLoS Computational Biology, 8(7), [e1002575].
Jol, S. J., Kümmel, A., Terzer, M., Stelling, J., & Heinemann, M. (2012). System-level insights into yeast metabolism by thermodynamic analysis of elementary flux modes. PLoS Computational Biology, 8(3), [e1002415].
Lee, S. S., Avalos Vizcarra, I., Huberts, D. H. E. W., Lee, L. P., & Heinemann, M. (2012). Whole lifespan microscopic observation of budding yeast aging through a microfluidic dissection platform. Proceedings of the National Academy of Sciences of the United States of America, 109(13), 4916-4920.
Fromm, S. A., Truffault, V., Kamenz, J., Braun, J. E., Hoffmann, N. A., Izaurralde, E., & Sprangers, R. (2012). The structural basis of Edc3‐ and Scd6‐mediated activation of the Dcp1:Dcp2 mRNA decapping complex. The EMBO Journal, 31, 279-290.


Urban, P. L., Schmidt, A. M., Fagerer, S. R., Amantonico, A., Ibañez, A., Jefimovs, K., Heinemann, M., & Zenobi, R. (2011). Carbon-13 labelling strategy for studying the ATP metabolism in individual yeast cells by micro-arrays for mass spectrometry. Molecular BioSystems, 7(10), 2837-2840.
Costenoble, R., Picotti, P., Reiter, L., Stallmach, R., Heinemann, M., Sauer, U., & Aebersold, R. (2011). Comprehensive quantitative analysis of central carbon and amino-acid metabolism in Saccharomyces cerevisiae under multiple conditions by targeted proteomics. Molecular Systems Biology, 7(1), 464-1-464-13. [464].
Volkmer, B., & Heinemann, M. (2011). Condition-dependent cell volume and concentration of Escherichia coli to facilitate data conversion for systems biology modeling. PLoS ONE, 6(7), [23126].
Heinemann, M., & Sauer, U. (2011). From good old biochemical analyses to high-throughput omics measurements and back. Current Opinion in Biotechnology, 22(1), 1-2.
Bujara, M., Schümperli, M., Pellaux, R., Heinemann, M., & Panke, S. (2011). Optimization of a blueprint for in vitro glycolysis by metabolic real-time analysis. Nature Chemical Biology, 7(5), 271-277.
Heinemann, M., & Zenobi, R. (2011). Single cell metabolomics. Current Opinion in Biotechnology, 22(1), 26-31.
Sturm, A., Heinemann, M., Arnoldini, M., Benecke, A., Ackermann, M., Benz, M., Dormann, J., & Hardt, W-D. (2011). The cost of virulence: retarded growth of Salmonella Typhimurium cells expressing type III secretion system 1. PLoS Pathogens, 7(7), [1002143].
Milias-Argeitis, A., Summers, S., Stewart-Ornstein, J., Zuleta, I., Pincus, D., El-Samad, H., Khammash, M., & Lygeros, J. (2011). In silico feedback for in vivo regulation of a gene expression circuit. Nature Biotechnology, 29, 1114-1116.
Ruess, J., Milias-Argeitis, A., Summers, S., & Lygeros, J. (2011). Moment estimation for chemically reacting systems by extended Kalman filtering. Journal of Chemical Physics, 135(16), [165102].


Kotte, O., Zaugg, J. B., & Heinemann, M. (2010). Bacterial adaptation through distributed sensing of metabolic fluxes. Molecular Systems Biology, 82(9), 1492-1493. [355].
Kummel, A., Ewald, J. C., Fendt, S-M., Jol, S. J., Picotti, P., Aebersold, R., Sauer, U., Zamboni, N., & Heinemann, M. (2010). Differential glucose repression in common yeast strains in response to HXK2 deletion. Fems Yeast Research, 10(3), 322-332.
Bujara, M., Schümperli, M., Billerbeck, S., Heinemann, M., & Panke, S. (2010). Exploiting Cell-Free Systems: Implementation and Debugging of a System of Biotransformations. Biotechnology and Bioengineering, 106(3), 376-389.
Heinemann, M., & Sauer, U. (2010). Systems biology of microbial metabolism. Current Opinion in Microbiology, 13(3), 337-343.
Jol, S. J., Kümmel, A., Hatzimanikatis, V., Beard, D. A., & Heinemann, M. (2010). Thermodynamic calculations for biochemical transport and reaction processes in metabolic networks. Biophysical Journal, 99(10), 3139-3144.
Kleijn, R., Fendt, S-M., Schuetz, R., Heinemann, M., Zamboni, N., & Sauer, U. (2010). Transcriptional control of metabolic fluxes and computational identification of the governing principles. Febs Journal, 277, 27-27.
Ramponi, F., Chatterjee, D., Milias-Argeitis, A., Hokayem, P., & Lygeros, J. (2010). Attaining mean square boundedness of a marginally stable stochastic linear system with a bounded control input. IEEE Transactions on Automatic Control, 55(10), 2414-2418.
Milias-Argeitis, A., Porreca, R., Summers, S., & Lygeros, J. (2010). Bayesian model selection for the yeast GATA-factor network: A comparison of computational approaches. In 2010 49th IEEE Conference on Decision and Control, CDC 2010 (pp. 3379-3384). [5717307]


Kotte, O., & Heinemann, M. (2009). A divide-and-conquer approach to analyze underdetermined biochemical models. Bioinformatics, 25(4), 519-525.
Lee, S. S., Vizcarra, I. A., Lee, L. P., & Heinemann, M. (2009). Long-term monitoring of yeast cell division via elastic micro-pad. In Proceedings of Conference, MicroTAS 2009 - The 13th International Conference on Miniaturized Systems for Chemistry and Life Sciences (pp. 478-480). Chemical and Biological Microsystems Society .
Graaf, A. A. D., Freidig, A. P., Roos, B. D., Jamshidi, N., Heinemann, M., Rullmann, J. A. C., Hall, K. D., Adiels, M., & Ommen, B. V. (2009). Nutritional Systems Biology Modeling: From Molecular Mechanisms to Physiology. PLoS Computational Biology, 5(11), [e1000554].
Cook, G. M., Berney, M., Gebhard, S., Heinemann, M., Cox, R. A., Danilchanka, O., & Niederweis, M. (2009). Physiology of mycobacteria. Advances in microbial physiology, 55, 81-182.
Heinemann, M., & Panke, S. (2009). Synthetic Biology: Putting Engineering into Bioengineering. In P. Fu, & S. Panke (Eds.), Systems Biology and Synthetic Biology (pp. 387-409). Wiley.
Cinquemani, E., Milias-Argeitis, A., Summers, S., & Lygeros, J. (2009). Local identification of piecewise deterministic models of genetic networks. In Hybrid Systems: Computation and Control - 12th International Conference, HSCC 2009, Proceedings (Vol. 5469, pp. 105-119). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5469).


Herrgård, M. J., Swainston, N., Dobson, P., Dunn, W. B., Arga, K. Y., Arvas, M., Blüthgen, N., Borger, S., Costenoble, R., Heinemann, M., Hucka, M., Novère, N. L., Li, P., Liebermeister, W., Mo, M. L., Oliveira, A. P., Petranovic, D., Pettifer, S., Simeonidis, E., ... Kell, D. B. (2008). A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology. Nature Biotechnology, 26(10), 1155-1160.
Zamboni, N., Kümmel, A., & Heinemann, M. (2008). anNET: a tool for network-embedded thermodynamic analysis of quantitative metabolome data. Bmc Bioinformatics, 9(199), [199].
Amantonico, A., Oh, J. Y., Sobek, J., Heinemann, M., & Zenobi, R. (2008). Mass Spectrometric Method for Analyzing Metabolites in Yeast with Single Cell Sensitivity. Angewandte Chemie International Edition, 47(29), 5382-5385.
Cinquemani, E., Milias-Argeitis, A., & Lygeros, J. (2008). Identification of genetic regulatory networks: A stochastic hybrid approach. In Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 17, No. 1 PART 1). Elsevier.
Cinquemani, E., Milias-Argeitis, A., Summers, S., & Lygeros, J. (2008). Stochastic dynamics of genetic networks: modelling and parameter identification. Bioinformatics (Oxford, England), 24(23), 2748-2754.


Makart, S., Heinemann, M., & Panke, S. (2007). Characterization of the AlkS/P-alkB-expression system as an efficient tool for the production of recombinant proteins in Escherichia coli fed-batch fermentations. Biotechnology and Bioengineering, 96(2), 326-336.
Sauer, U., Heinemann, M., & Zamboni, N. (2007). Genetics - Getting closer to the whole picture. Science, 316(5824), 550-551.
Hübscher, J., Jansen, A., Kotte, O., Schäfer, J., Majcherczyk, P. A., Harris, L. G., Bierbaum, G., Heinemann, M., & Berger-Bächi, B. (2007). Living with an imperfect cell wall: compensation of femAB inactivation in Staphylococcus aureus. BMC Genomics, 8, [307].


Seggewib, J., Becker, K., Kotte, O., Eisenacher, M., Khoschkhoi Yazdi, M. R., Fischer, A., McNamara, P., Proctor, R. A., Peters, G., Heinemann, M., & von Eiff, C. (2006). Detailed survey of genome-wide expression differences between a Staphylococcus aureus mutant displaying the small colony variant phenotype and its parental strain. International journal of medical microbiology, 296, 132-133.
Bechtold, M., Makart, S., Heinemann, M., & Panke, S. (2006). Integrated operation of continuous chromatography and biotransformations for the generic high yield production of fine chemicals. Journal of Biotechnology, 124(1), 146-162.
Kümmel, A., Panke, S., & Heinemann, M. (2006). Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data. Molecular Systems Biology, 2, 2006.0034.
Seggewiß, J., Becker, K., Kotte, O., Eisenacher, M., Khoschkhoi Yazdi, M. R., Fischer, A., McNamara, P., Laham, N. A., Proctor, R., Peters, G., Heinemann, M., & Eiff, C. V. (2006). Reporter Metabolite Analysis of Transcriptional Profiles of a Staphylococcus aureus Strain with Normal Phenotype and Its Isogenic hemB Mutant Displaying the Small-Colony-Variant Phenotype. Journal of Bacteriology, 188(22), 7765-7777.
Davidescu, F. P., Madsen, H., Schümperli, M., Heinemann, M., Panke, S., & Jørgensen, S. B. (2006). Stochastic grey box modeling of the enzymatic biochemical reaction network of E. coli mutants. In Proceedings of the 16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering (21 ed., pp. 161-166). Elsevier.
Bechtold, M., Heinemann, M., & Panke, S. (2006). Suitability of teicoplanin-aglycone bonded stationary phase for simulated moving bed enantio separation of racemic amino acids employing composition-constrained eluents. Journal of Chromatography A, 1113(1-2), 167-176.
Heinemann, M., & Panke, S. (2006). Synthetic biology--putting engineering into biology. Bioinformatics, 22(22), 2790-2799.
Kümmel, A., Panke, S., & Heinemann, M. (2006). Systematic assignment of thermodynamic constraints in metabolic network models. Bmc Bioinformatics, 7(512).,


Schumperli, M., Heinemann, M., Gomolka, S., Kummel, A., & Panke, S. (2005). A new approach for the production of DHAP: The system of biotransformations. Journal of Biotechnology, 118, S90-S90.
Kummel, A., Schumperli, M., & Heinemann, M. (2005). Design of a system of biotransformations by means of stoichiometric network analysis. Journal of Biotechnology, 118, S105-S105.
Heinemann, M., Kümmel, A., Ruinatscha, R., & Panke, S. (2005). In Silico Genome-Scale Reconstruction and Validation of the Staphylococcus aureus Metabolic Network. Biotechnology and Bioengineering, 92(7), 850-864.
Heinemann, M., Meinberg, H., Büchs, J., Koß, H-J., & Ansorge-Schumacher, M. B. (2005). Method for Quantitative Determination of Spatial Polymer Distribution in Alginate Beads Using Raman Spectroscopy. Applied Spectroscopy, 59(3), 280-285.
Kluge, J., Kummel, A., Panke, S., & Heinemann, M. (2005). Model-based identification of regulation patterns controlling metabolic redundancy in central carbon metabolism. Journal of Biotechnology, 118, S3-S3.
Trivedi, A., Heinemann, M., Spiess, A. C., Daussmann, T., & Büchs, J. (2005). Optimization of Adsorptive Immobilization of Alcohol Dehydrogenases. Journal of Bioscience and Bioengineering, 99(4), 340-347.
Buthe, A., Recker, T., Heinemann, M., Hartmeier, W., Büchs, J., & Ansorge-Schumacher, M. B. (2005). pH-optima in lipase-catalysed esterification. Biocatalysis and Biotransformation, 23(5), 307-314.


Panke, S., Kümmel, A., Schümperli, M., & Heinemann, M. (2004). Industrial multi-step biotransformations. Chimica Oggi-Chemistry Today, 22(9), 44-47.
Heinemann, M., Limper, U., & Büchs, J. (2004). New insights in the spatially resolved dynamic pH measurement in macroscopic large absorbent particles by confocal laser scanning microscopy. Journal of Chromatography A, 1024(1), 45-53.
Ferloni, C., Heinemann, M., Hummel, W., Daussmann, T., & Büchs, J. (2004). Optimization of enzymatic gas-phase reactions by increasing the long-term stability of the catalyst. Biotechnology Progress, 20(3), 975-978.


Heinemann, M., Kümmel, A., Giesen, R., Ansorge-Schumacher, M. B., & Büchs, J. (2003). Experimental and Theoretical Analysis of Phase Equilibria in a Two-phase System Used for Biocatalytic Esterifications. Biocatalysis and Biotransformation, 21(3), 115-121.


Heinemann, M., Wagner, T., Doumèche, B., Ansorge-Schumacher, M., & Büchs, J. (2002). A new approach for the spatially resolved qualitative analysis of the protein distribution in hydrogel beads based on confocal laser scanning microscopy. Biotechnology Letters, 24(10), 845-850.
Doumèche, B., Heinemann, M., Büchs, J., Hartmeier, W., & Ansorge-Schumacher, M. B. (2002). Enzymatic catalysis in gel-stabilized two-phase systems: improvement of the solvent phase. Journal of Molecular Catalysis B: Enzymatic, 18(1), 19-27.
Last modified:01 February 2021 11.27 a.m.