Habeck, Michael, Dr.


  • 1993-1999 Physics studies at the University of Siegen and the University of Heidelberg
  • 2001-2004 PhD work at Institut Pasteur, Paris
  • 2004-2005 Postdoc Institut Pasteur, Paris
  • 2005-2009 Research scientist at the Max-Planck-Institute for Biological Cybernetics and the Max-Planck-Institute for Developmental Biology, Tübingen
  • 2009-2012 Leader of an independent research group (Emmy Noether Programme) at the Max-Planck-Institute for Developmental Biology, Tübingen
  • 2013 – 2014 Leader of an independent research group (Emmy Noether Programme) at the University of Göttingen
  • since 2015 Project leader at Max Planck Institute for Biophysical Chemistry and University of Göttingen



Major Research Interests

I am broadly interested in Bayesian inference and its application to biological and other real- world data. I view probability theory as the mathematical framework for making consistent inferences and predictions from incomplete and uncertain information. Therefore, Bayesian methods are powerful tools to support scientific inference and to solve engineering problems. My previous and current research focuses on three highly interconnected topics: Computational structural biology, Bayesian computation and Statistical physics.

My group is mainly involved in the development of a Bayesian probabilistic approach to biomolecular structure determination which we call Inferential Structure Determination (ISD). Over the years, ISD has matured into a powerful tool for macromolecular structure calculation from NMR, X-ray, cryo-EM and other structural data by means of Markov chain Monte Carlo simulation. Moreover, we maintain a keen interest in developing new methods for cryo-EM data analysis and image processing. We are currently developing tools to model large and dynamic systems (protein complexes, chromosomes) and work on new algorithms for general Bayesian computation.




Homepage Department/Research Group

http://www.stochastik.math.uni-goettingen.de/habeck



Selected Recent Publications



  • Chen YL, Habeck M (2017) Data-driven coarse graining of large biomolecular structures. PloS one, 12(8), e0183057

  • Carstens S, Nilges M, Habeck M (2016) Inferential structure determination of chromosomes from single-cell Hi-C data. PLoS computational biology, 12(12), e1005292

  • Habenstein B, Loquet A, Hwang S, Giller K, Vasa SK, Becker S, Habeck M, Lange A (2015) Hybrid structure of the type 1 pilus of uropathogenic Escherichia coli. Angewandte Chemie, 127(40), 11857-11861

  • Shahid S, Bardiaux B, Franks T, Krabben L, Habeck M, Rossum B, Linke D (2012) Membrane-protein structure determination by solid-state NMR spectroscopy of microcrystals, Nature Methods 9, 1212-7

  • Rieping W, Habeck M, Nilges M (2005) Inferential structure determination. Science 309, 303-6