Liepe, Juliane, Dr.

Research Group Leader at the Department of Molecular Biology at the Max Planck Institute for Multidisciplinary Sciences

  • Since 2017
    Research Group Leader Quantitative and Systems Biology at the Max-Planck Institute for Biophysical Chemistry (Göttingen, Germany)
  • 2013 - 2016
    NC3Rs David Sainsbury Research Fellow at Imperial College London (UK)
  • 2013
    Postdoc in the group of Theoretical Systems Biology at Imperial College London (UK)
  • 2009 - 2013
    PhD in the group of Theoretical Systems Biology at Imperial College London (UK).
  • 2008 - 2009
    M.Sc. in Bioinformatics and Theoretical Systems Biology at Imperial College London (UK)
  • 2006 - 2008
    Studies of Mathematics at University of Potsdam (Germany)
  • 2004 - 2008
    Diploma in Biochemistry at University of Potsdam (Germany)

  • Major Research Interests

    The Quantitative and Systems Biology group employs in silico approaches, using in vitro and ex vivo and in vivo experimental data, to study the pathways of the proteasome that regulate the human immune response.
    The proteasome is a multicomplex enzyme that catalyses protein degradation. Apart from its function in protein metabolism, the proteasome regulates the immune system through antigen presentation, where the proteasome produces most of the epitopes presented in the MHC-class I pathway. These epitopes can be generated by simple cut, or cut-and-paste events. Latter so-called proteasome-generated spliced peptides (PSPs) represent more than one third of all epitopes bound to MHC-class I molecules.

    We have developed a set of mathematical and bioinformatics tools to study the details of proteasome-catalysed hydrolysis and peptide splicing and its importance in the MHC-class I pathway. This includes algorithms to identify PSPs from ex cellulo mass spectrometry data and methods to classify and characterise PSPs. In the future this will result in the development of algorithms to predict PSP sequences.
    Our group therefore focuses on the development and application of diverse approaches, ranging from efficient mass spectrometry search algorithms and machine learning algorithms to dynamical modelling and model calibration approaches.

    The proteasome already is a target for therapeutic trails against cancer and infectious diseases, but its full potential still needs to be explored. This research and the in silico tools developed here will aid such translational aspects and advance the ongoing research in systems immunology.

    Homepage Department/Research Group

    Selected Recent Publications

  • A large fraction of HLA class I ligands are proteasome-generated spliced peptides.
    Liepe J, Marino F, Sidney J, Jeko A, Bunting DE, Sette A, Kloetzel PM, Stumpf MPH, Heck AJR and Mishto M
    Science. 2016 October. DOI: 10.1126/science.aaf4384

  • Systems analysis of the dynamic inflammatory response to tissue damage reveals spatio-temporal properties of the wound attractant gradient.
    Weavers H*, Liepe J*, Sim A, Wood W, Martin P and Stumpf MPH
    Current Biology. 2016 July. DOI:

  • Accurate reconstruction of cell and particle tracks from 3D live imaging data.
    Liepe J*, Sim A*, Weavers H, Ward L, Martin P and Stumpf MPH
    Cell Systems. 2016 July. DOI:

  • Quantitative time-resolved analysis reveals intricate, differential regulation of standard- and immuno-proteasomes.
    Liepe J, Holzhütter HG, Bellavista E, Kloetzel PM, Stumpf MPH and Mishto M.
    elife. 2015 Sep 22;4. doi: 10.7554/eLife.07545.

  • A Framework for Parameter Estimation and Model Selection From Experimental Data in Systems Biology Using Approximate Bayesian Computation.
    Liepe J, Kirk P, Filippi S, Toni T, Stumpf MPH
    Nature Protocols 2014 Jan; 9: 439?456. doi:10.1038/nprot.2014.025.