english version
Nächster Vortrag im Stochastischen Kolloquium:
24.01.2018, 11:15, Prof. Wilfrid S. Kendall (University of Warwick)

"A Dirichlet Form approach to MCMC Optimal Scaling" (Abstract).
Statistics Meets Friends: The workshop "Statistics Meets Friends - from biophysics to inverse problems and back -" took place in Göttingen from November 29th to December 1st, 2017 (press release).
Dr. Michael Habeck
Foto Dr. Michael Habeck

Institut für Mathematische Stochastik

Goldschmidtstrasse 7
37077 Göttingen

Room:Raum 2.191: Gebaeude GZG: Goldschmidtstr. 3-5 (GZG)
Phone:+49 551 39 172136
Research statement

I develop Bayesian statistical methods, with application to structural biology and biological physics. I also maintain interests in various related areas of statistical physics and biology, including statistical analysis of biomolecular structures and sequences, probability theory, machine learning, image processing and Bayesian computation.


Professional positions
2014-presentProject leader at Max Planck Institute for Biophysical Chemistry and Felix Bernstein Institute for Mathematical Statistics in the Biosciences
2013-2014Leader of an independent research group (Emmy Noether Programme) at Institute for Mathematical Stochastics
2009-2012Leader of an independent research group (Emmy Noether Programme) at Department of Protein Evolution (MPI for Developmental Biology, Tübingen)
2005-2009Research scientist at Department of Empirical Inference (MPI for Biological Cybernetics) and Department of Protein Evolution (MPI for Developmental Biology, Tübingen)
2004-2005Postdoctoral work at Structural Bioinformatics Unit, Institut Pasteur, Paris, France


2004PhD in Biophysics at Regensburg University, Germany
2001-2004PhD work at Institut Pasteur, Paris
1999Diplom in Physics, Heidelberg University, Germany


2010-2014Baden-Wuerttemberg Stiftung
2009-2014Emmy Noether-Programme (DFG)


Full publication list at google scholar

Selected publications:


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

M. Habeck: Bayesian estimation of free energies from equilibrium simulations. Physical Review Letters 109:100601

V. S. Honndorf*, N. Coudevylle*, S. Laufer, S. Becker, C. Griesinger* and M. Habeck*: Inferential NMR/X-ray based structure determination of a dibenzo[a,d]cyclo-heptenone inhibitor/p38 MAP kinase complex in solution. Angewandte Chemie 51:2359-62


I. Kalev and M. Habeck. HHfrag: HMM-based fragment detection using HHpred. Bioinformatics 27:3110-6

M. Hirsch, B. Schölkopf, and M. Habeck: A Blind Deconvolution Approach for Improving the Resolution of Cryo-EM Density Maps. Journal of Computational Biology 18:335-346


M. Bayrhuber*, T. Meins*, M. Habeck*, S. Becker*, K. Giller, S. Villinger, C. Vonrhein, C. Griesinger*, M. Zweckstetter*, and K. Zeth*: Structure of the human voltage-dependent anion channel. PNAS 105:15370-5 doi:10.1073/pnas.0808115105


M. Habeck: Bayesian reconstruction of the density of states. Physical Review Letters 98:200601

W. Rieping*, M. Habeck*, B. Bardiaux, A. Bernard, T. E. Malliavin, and M. Nilges: ARIA2: automated NOE assignment and data integration in NMR structure calculation. Bioinformatics 23:381


M. Habeck*, W. Rieping*, and M. Nilges: Weighting of experimental evidence in macromolecular structure determination. PNAS 103:1756-61


W. Rieping*, M. Habeck*, and M. Nilges: Inferential structure determination. Science 309:303-6

M. Habeck, M. Nilges, and W. Rieping: Replica-exchange Monte Carlo scheme for Bayesian data analysis. Physical Review Letters 94:018105