Prof. Dr. Ralf Reski

Projects within livMatS

• Dissipative systems engineering: Chemically fueled active molecular systems

Doctoral Researchers (first supervisor)

• Stella Milferstädt
  

Publications in livMatS

• Expression of a human cDNA in moss results in spliced mRNAs and fragmentary protein isoforms*
  Top, O., Milferstaedt, S. W., van Gessel, N., Hoernstein, S. N., Özdemir, B., Decker, E. L., & Reski, R. (2021). Expression of a human cDNA in moss results in spliced mRNAs and fragmentary protein isoforms. Communications biology, 4(1), 1-13. doi: 10.1038/s42003-021-02486-3
• Natural Products from Bryophytes: From BasicBiology to Biotechnological Applications
  Horn, A., Pascal, A., Lončarević, I., Volpatto Marques, R., Lu, Y., Miguel, S., Bourgaud, F., Thorsteinsdóttir, M., Cronberg, N., Becker, J. D., Reski, R. & Simonsen, H. T. (2021). Natural Products from Bryophytes: From Basic Biology to Biotechnological Applications. Critical Reviews in Plant Sciences, 1-27. doi: 10.1080/07352689.2021.1911034
• Medium optimization for biomass production of three peat moss (Sphagnum L.) species using fractional factorial design and response surface methodology*
  Heck, M.A., Melkova, I., Posten, C., Decker, E.L., Reski, R. (2021): Medium optimization for biomass production of three peat moss (Sphagnum L.) species using fractional factorial design and response surface methodology. Bioresource Technology Reports 15, 100729. doi: 10.1016/j.biteb.2021.100729
• Automated and Semi-Automated Enhancement, Segmentation and Tracing of Cytoskeletal Networks in Microscopic Images: A Review*
  Özdemir, B., & Reski, R. (2021). Automated and Semi-Automated Enhancement, Segmentation and Tracing of Cytoskeletal Networks in Microscopic Images: A Review. Computational and Structural Biotechnology Journal. doi: 10.1016/j.csbj.2021.04.019
• Stable Protein Sialylation in Physcomitrella
  Bohlender, L. L., Parsons, J., Hoernstein, S. N., Rempfer, C., Ruiz-Molina, N., Lorenz, T., Rodriguez-Jahnke, F., Figl, R., Fode, B., Altmann, F., Reski, R., & Decker, E. L. (2020). Stable Protein Sialylation in Physcomitrella. Frontiers in plant science, 11. doi: 10.3389/fpls.2020.610032.
• A NanoFE simulation-based surrogate machine learning model to predict mechanical functionality of protein networks from live confocal imaging
  Asgharzadeh, P., Birkhold, A. I., Trivedi, Z., Özdemir, B., Reski, R., & Röhrle, O. (2020). A NanoFE simulation-based surrogate machine learning model to predict mechanical functionality of protein networks from live confocal imaging. Computational and structural biotechnology journal, 18, 2774-2788. doi: 10.1016/j.csbj.2020.09.024
• Expression of a human cDNA in moss results in spliced mRNAs and fragmentary protein isoforms*
  Top, O., Milferstaedt, S. W., van Gessel, N., Hoernstein, S. N., Özdemir, B., Decker, E. L., & Reski, R. (2020). Expression of a human cDNA in moss results in spliced mRNAs and fragmentary protein isoforms. bioRxiv. doi: 10.1101/2020.09.30.320721
• Axenic in vitro cultivation of 19 peat moss (Sphagnum L.) species as a resource for basic biology, biotechnology, and paludiculture*
  Heck, M. A., Lüth, V. M., van Gessel, N., Krebs, M., Kohl, M., Prager, A., Joosten H., & Reski, R. (2020). Axenic in vitro cultivation of 19 peat moss (Sphagnum L.) species as a resource for basic biology, biotechnology, and paludiculture. New Phytologist. doi: 10.1111/nph.16922
• Mosses in biotechnology*
  Decker, E. L., & Reski, R. (2020). Mosses in biotechnology. Current opinion in biotechnology, 61, 21-27. doi: 10.1016/j.copbio.2019.09.021
• Biosurface properties and lead adsorption in a clone of Sphagnum palustre (Mosses): Towards a unified protocol of biomonitoring of airbone heavy metal pollution
  Di Palma, A., González, A. G., Adamo, P., Giordano, S., Reski, R., & Pokrovsky, O. S. (2019). Biosurface properties and lead adsorption in a clone of Sphagnum palustre (Mosses): Towards a unified protocol of biomonitoring of airborne heavy metal pollution. Chemosphere, 236, 124375. doi: 10.1016/j.chemosphere.2019.124375
  
  
  * Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – EXC-2193/1 – 390951807