• Thi Doan, Dieu, Andreas Kremling, and Jérôme Morchain. "A Monte‐Carlo approach for the simulation of microbial population dynamics in an heterogeneous scale‐down bioreactor." AIChE Journal (2024): e18358. DOI:


  • Vogeleer, P., Millard, P., Arbulú, A. S. O., Pflüger-Grau, K., Kremling, A., & Létisse, F. (2023). Metabolic impact of heterologous protein production in Pseudomonas putida: Insights into carbon and energy flux control. Metabolic Engineering. DOI: 10.1016/j.ymben.2023.10.005
  • Dvořák, P., Galvão, T. C., Pflüger‐Grau, K., Banks, A. M., de Lorenzo, V., & Jiménez, J. I. (2023). Water potential governs the effector specificity of the transcriptional regulator XylR of Pseudomonas putidaEnvironmental Microbiology. DOI: 10.1111/1462-2920.16342
  • Eshtewy, N.A.; Scholz, L.; Kremling, A. (2023) Parameter Estimation for a Kinetic Model of a Cellular System Using Model Order Reduction Method. Mathematics11, 699. DOI: 10.3390/math11030699


  • Beentjes, M., Ortega-Arbulú, A. S., Löwe, H., Pflüger-Grau, K., & Kremling, A. (2022). Targeting Transcriptional and Translational Hindrances in a Modular T7RNAP Expression System in Engineered Pseudomonas putidaACS Synthetic Biology. DOI: 10.1021/acssynbio.2c00295
  • Hobmeier, K., Oppermann, M., Kremling, A., Pflüger-Grau, K., Kunte, H. J. & Marin Sanguino, A. (2022). Metabolic engineering of Halomonas elongata: Ectoine secretion is increased by demand and supply driven approaches. Frontiers in Microbiology13, 1-13. DOI: 10.3389/fmicb.2022.968983
  • Doan, D. T., Hoang, M. D., Heins, A. L. & Kremling, A. Applications of Coarse-grained Models in Metabolic Engineering. Frontiers in Molecular Biosciences, 90. DOI: 10.3389/fmolb.2022.806213
  • Kratzl, F., Kremling, A., & Pflüger‐Grau, K. (2022). Streamlining of a synthetic co‐culture towards an individually controllable one‐pot process for polyhydroxyalkanoate production from light and CO2. Engineering in Life Sciences. DOI: 10.1002/elsc.202100156


  • Kremling, Andreas. "A counting-strategy together with a spatial structured model describes RNA polymerase and ribosome availability in Escherichia coli." Metabolic Engineering 67 (2021): 145-152. DOI: 10.1016/j.ymben.2021.06.006
  • Löwe, H., Kremling, A. (2021). In-Depth Computational Analysis of Natural and Artificial Carbon Fixation Pathways. BioDesign Research Vol. 2021. DOI: 10.34133/2021/9898316
  • Löwe, H., Beentjes, M., Pflüger-Grau, K., & Kremling, A. (2021). Trehalose production by Cupriavidus necator from CO2 and hydrogen gas. Bioresource Technology, 319, 124169. DOI: 10.1016/j.biortech.2020.124169


  • Hobmeier, K., Goëss, M. C., Sehr, C., Schwaminger, S., Berensmeier, S., Kremling, A., ... & Marin-Sanguino, A. (2020). Anaplerotic pathways in Halomonas elongata: the role of the sodium gradient. Frontiers in microbiology, 11, 2124. DOI:10.3389/fmicb.2020.561800
  • Löwe, H., Sinner, P., Kremling, A., & Pflüger‐Grau, K. (2020). Engineering sucrose metabolism in Pseudomonas putida highlights the importance of porins. Microbial biotechnology, 13(1), 97-106. DOI: 10.1111/1751-7915.13283
  • Hobmeier, K., Löwe, H., Liefeldt, S., Kremling, A., & Pflüger-Grau, K. (2020). A Nitrate-Blind P. putida Strain Boosts PHA Production in a Synthetic Mixed Culture. Frontiers in Bioengineering and Biotechnology, 8, 486.DOI: 10.3389/fbioe.2020.00486 
  • Bromig, L., Kremling, A., & Marin-Sanguino, A. (2020). Understanding biochemical design principles with ensembles of canonical non-linear models. PloS one, 15(4), e0230599. DOI: 10.1371/journal.pone.0230599


  • Wagner, S. G., Mähler, C., Polte, I., von Poschinger, J., Löwe, H., Kremling, A., & Pflüger-Grau, K. (2019). An automated and parallelised DIY-dosing unit for individual and complex feeding profiles: Construction, validation and applications. PloS one14(6), e0217268. DOI: 10.1371/journal.pone.0217268


  • Hortsch, S. K., & Kremling, A. (2018). Adjusting Noise in the Genetic Toggle Switch through Stochastic Circuit Design. IFAC-PapersOnLine51(19), 68-71. DOI: 10.1016/j.ifacol.2018.09.045
  • Kremling, A., Geiselmann, J., Ropers, D., & de Jong, H. (2018). An ensemble of mathematical models showing diauxic growth behaviour. BMC systems biology12(1), 1-16. DOI: 10.1186/s12918-018-0604-8
  • Kyselova, L., Kreitmayer, D., Kremling, A., & Bettenbrock, K. (2018). Type and capacity of glucose transport influences succinate yield in two-stage cultivations. Microbial cell factories17(1), 1-15. DOI: 10.1186/s12934-018-0980-1
  • Löwe, H., Sinner, P., Kremling, A., & Pflüger‐Grau, K. (2020). Engineering sucrose metabolism in Pseudomonas putida highlights the importance of porins. Microbial biotechnology13(1), 97-106. DOI: 10.1111/1751-7915.13283
  • Wagner, S. G., Ziegler, M., Löwe, H., Kremling, A., & Pflüger-Grau, K. (2018). pTRA–A reporter system for monitoring the intracellular dynamics of gene expression. PloS one13(5), e0197420. DOI: 10.1371/journal.pone.0197420
  • Hortsch, S. K., & Kremling, A. (2018). Characterization of noise in multistable genetic circuits reveals ways to modulate heterogeneity. PloS one13(3), e0194779. DOI: 10.1371/journal.pone.0194779


  • Löwe, H., Hobmeier, K., Moos, M., Kremling, A., & Pflüger-Grau, K. (2017). Photoautotrophic production of polyhydroxyalkanoates in a synthetic mixed culture of Synechococcus elongatus cscB and Pseudomonas putida cscAB. Biotechnology for biofuels10(1), 1-11. DOI: 10.1186/s13068-017-0875-0
  • Löwe, H., Schmauder, L., Hobmeier, K., Kremling, A., & Pflüger‐Grau, K. (2017). Metabolic engineering to expand the substrate spectrum of Pseudomonas putida toward sucrose. Microbiologyopen6(4), e00473. DOI: 10.1002/mbo3.473
  • Löwe, H., Kremling, A., & Pflüger-Grau, K. (2017). Bioplastik aus Licht und Luft–das Konzept einer synthetischen Ko-Kultur. Biospektrum23(3), 338-340. DOI: 10.1007/s12268-017-0802-8


  • Valderrama-Gomez, M. A., et al. "Application of theoretical methods to increase succinate production in engineered strains." Bioprocess and biosystems engineering 40.4 (2017): 479-497. DOI: 10.1007/s00449-016-1729-z
  • Löwe, H., Kremling, A., & Marin-Sanguino, A. (2016). Time hierarchies and model reduction in canonical non-linear models. Frontiers in genetics7, 166. DOI: 10.3389/fgene.2016.00166
  • Hahl, S. K., & Kremling, A. (2016). A comparison of deterministic and stochastic modeling approaches for biochemical reaction systems: On fixed points, means, and modes. Frontiers in genetics7, 157. DOI: 10.3389/fgene.2016.00157