Heidelberg, Germany
Heidelberg, Germany

Time filter

Source Type

Barends T.R.M.,MPI for Medical Research | Brosi R.W.W.,Free University of Berlin | Steinmetz A.,MPI for Medical Research | Scherer A.,MPI for Medical Research | And 9 more authors.
Acta Crystallographica Section D: Biological Crystallography | Year: 2013

Hsp70 chaperones assist in a large variety of protein-folding processes in the cell. Crucial for these activities is the regulation of Hsp70 by Hsp40 cochaperones. DnaJ, the bacterial homologue of Hsp40, stimulates ATP hydrolysis by DnaK (Hsp70) and thus mediates capture of substrate protein, but is also known to possess chaperone activity of its own. The first structure of a complete functional dimeric DnaJ was determined and the mobility of its individual domains in solution was investigated. Crystal structures of the complete molecular cochaperone DnaJ from Thermus thermophilus comprising the J, GF and C-terminal domains and of the J and GF domains alone showed an ordered GF domain interacting with the J domain. Structure-based EPR spin-labelling studies as well as cross-linking results showed the existence of multiple states of DnaJ in solution with different arrangements of the various domains, which has implications for the function of DnaJ. © 2013 International Union of Crystallography.


Galli L.,German Electron Synchrotron | Galli L.,University of Hamburg | Son S.-K.,German Electron Synchrotron | Son S.-K.,Hamburg Center for Ultrafast Imaging | And 19 more authors.
IUCrJ | Year: 2015

X-ray free-electron lasers (XFELs) show great promise for macromolecular structure determination from sub-micrometre-sized crystals, using the emerging method of serial femtosecond crystallography. The extreme brightness of the XFEL radiation can multiply ionize most, if not all, atoms in a protein, causing their scattering factors to change during the pulse, with a preferential 'bleaching' of heavy atoms. This paper investigates the effects of electronic damage on experimental data collected from a Gd derivative of lysozyme microcrystals at different X-ray intensities, and the degree of ionization of Gd atoms is quantified from phased difference Fourier maps. A pattern sorting scheme is proposed to maximize the ionization contrast and the way in which the local electronic damage can be used for a new experimental phasing method is discussed. © 2015.


PubMed | EMBL, MPI for Medical Research, Max Planck Institute for Medical Research, Uppsala University and 2 more.
Type: Journal Article | Journal: IUCrJ | Year: 2015

X-ray free-electron lasers (XFELs) show great promise for macromolecular structure determination from sub-micrometre-sized crystals, using the emerging method of serial femtosecond crystallography. The extreme brightness of the XFEL radiation can multiply ionize most, if not all, atoms in a protein, causing their scattering factors to change during the pulse, with a preferential bleaching of heavy atoms. This paper investigates the effects of electronic damage on experimental data collected from a Gd derivative of lysozyme microcrystals at different X-ray intensities, and the degree of ionization of Gd atoms is quantified from phased difference Fourier maps. A pattern sorting scheme is proposed to maximize the ionization contrast and the way in which the local electronic damage can be used for a new experimental phasing method is discussed.


Straehle C.-N.,University of Heidelberg | Koethe U.,University of Heidelberg | Knott G.,Ecole Polytechnique Federale de Lausanne | Briggman K.,U.S. National Institutes of Health | And 2 more authors.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition | Year: 2012

Watershed cuts are among the fastest segmentation algorithms and therefore well suited for interactive segmentation of very large 3D data sets. To minimize the number of user interactions (seeds) required until the result is correct, we want the computer to actively query the human for input at the most critical locations, in analogy to active learning. These locations are found by means of suitable uncertainty measures. We propose various such measures for watershed cuts along with a theoretical analysis of some of their properties. Extensive evaluation on two types of 3D electron microscopic volumes of neural tissue shows that measures which estimate the non-local consequences of new user inputs achieve performance close to an oracle endowed with complete knowledge of the ground truth. © 2012 IEEE.


Andres B.,University of Heidelberg | Kroeger T.,University of Heidelberg | Briggman K.L.,U.S. National Institutes of Health | Denk W.,MPI for Medical Research | And 4 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

We address the problem of partitioning a volume image into a previously unknown number of segments, based on a likelihood of merging adjacent supervoxels. Towards this goal, we adapt a higher-order probabilistic graphical model that makes the duality between supervoxels and their joint faces explicit and ensures that merging decisions are consistent and surfaces of final segments are closed. First, we propose a practical cutting-plane approach to solve the MAP inference problem to global optimality despite its NP-hardness. Second, we apply this approach to challenging large-scale 3D segmentation problems for neural circuit reconstruction (Connectomics), demonstrating the advantage of this higher-order model over independent decisions and finite-order approximations. © 2012 Springer-Verlag.


Kroeger T.,University of Heidelberg | Mikula S.,MPI for Medical Research | Denk W.,MPI for Medical Research | Koethe U.,University of Heidelberg | Hamprecht F.A.,University of Heidelberg
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

Segmentation schemes such as hierarchical region merging or correllation clustering rely on edge weights between adjacent (super-)voxels. The quality of these edge weights directly affects the quality of the resulting segmentations. Unstructured learning methods seek to minimize the classification error on individual edges. This ignores that a few local mistakes (tiny boundary gaps) can cause catastrophic global segmentation errors. Boundary evidence learning should therefore optimize structured quality criteria such as Rand Error or Variation of Information. We present the first structured learning scheme using a structured loss function; and we introduce a new hierarchical scheme that allows to approximately solve the NP hard prediction problem even for huge volume images. The value of these contributions is demonstrated on two challenging neural circuit reconstruction problems in serial sectioning electron microscopic images with billions of voxels. Our contributions lead to a partitioning quality that improves over the current state of the art. © 2013 Springer-Verlag.


Kroeger T.,University of Heidelberg | Mikula S.,MPI for Medical Research | Denk W.,MPI for Medical Research | Koethe U.,University of Heidelberg | Hamprecht F.A.,University of Heidelberg
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention | Year: 2013

Segmentation schemes such as hierarchical region merging or correllation clustering rely on edge weights between adjacent (super-)voxels. The quality of these edge weights directly affects the quality of the resulting segmentations. Unstructured learning methods seek to minimize the classification error on individual edges. This ignores that a few local mistakes (tiny boundary gaps) can cause catastrophic global segmentation errors. Boundary evidence learning should therefore optimize structured quality criteria such as Rand Error or Variation of Information. We present the first structured learning scheme using a structured loss function; and we introduce a new hierarchical scheme that allows to approximately solve the NP hard prediction problem even for huge volume images. The value of these contributions is demonstrated on two challenging neural circuit reconstruction problems in serial sectioning electron microscopic images with billions of voxels. Our contributions lead to a partitioning quality that improves over the current state of the art.

Loading MPI for Medical Research collaborators
Loading MPI for Medical Research collaborators