Courses

The module "Molecular Oncology" consists of a lecture describing biological properties of cancer. Topics include: biological processes relevant for cancer (such as signaling pathways, cell growth, proliferation, apoptosis, metabolism), cancer-specific aberrations, modern molecular approaches for investigating cancer.

In the module "Clinical Oncology" various clinicians present a current view of the disease "cancer". Topics include an overview over different tumor entities (including cancers of the blood, skin, breast, lung, liver, colon, endocrine system), treatment modalities (e.g. immunotherapy, radiation-based therapy, personalized medicine), diagnostics, pathology, clinical studies.

The module imparts detailed and in-depth the current state of science in the field of research on RNA-protein complexes, their structure and function, as well as the theoretical basics of current RNA-based research methods.

The module imparts detailed and in-depth the current state of science in the field of research on the regulation and control of the entire life cycle of proteins.

The module "Macromolecular Crystallography" consists of lectures, exercises and a practical course. The lecture series covers the following topics: Biophysical characterization of protein samples prior to crystallization; crystallization by various techniques, either by manual or high throughput operation; properties and production of X-rays and their production by means of X-ray generators and synchrotron sources; data collection with various detector systems; symmetry properties of molecules, point groups and space groups; description of the phase problem and solving this problem by means of multiple isomorphous replacement, anomalous diffraction and molecular replacement; improving experimentally determined phases by solvent flattening and molecular averaging; manual and automatic model building; refinement procedures and analysis of experimentally determined structures. In the exercises the topics covered in the lectures will be recapitulated with the help of problem sets. In the practical course, the students will carry out all  steps  discussed in the lecture series, which are necessary for the determination of a protein structure using lysozyme as an example; starting with the crystallization of the purified protein, data collection using the in-house diffractometer, the solution of the phase problem on the basis of the anomalous signal of the intrinsic sulfur atoms, model building, structure refinement and, finally, the analysis of the refined structure.

The module "Electron Microscopy and Image Processing in Structural Biology" includes a lecture section that explains the basics of electron microscopy and image processing. In a first step the components of the electron microscope, beam path, image formation and contrast transmission are explained. Subsequently, various methods of sample preparation for electron microscopy in structural biology will be discussed, as well as strategies for instrument alignment and data acquisition.

The second part of the lecture focuses on image data processing. The focus is on the principles of single part image analysis. This includes the alignment of image data, their classification and three-dimensional image reconstruction. We will discuss deNovo and iterative methods of 3D image reconstruction. The principles learned are then applied to special cases of analysis of 2D crystals and tomograms. Finally, micro-electron diffraction is presented as an alternative to X-ray structure analysis.

In the seminar part of the module some aspects of the lecture are deepened by means of case studies from the literature. The students read these case studies in advance. In this work they are guided through a questionnaire. You will work on some of the questions yourself in writing in advance. Most case studies are presented by one student at a time. All case studies are explained in a discussion. The participants develop a critical understanding of the advantages and limitations of the method. Some selected topics will be further explored in mathematical exercises.

In the "Oncology Seminar 1" selected original publications in cancer research are read and critically discussed. Participants are strongly advised to concurrently attend the lecture "Molecular Oncology".

In the "Oncology Seminar 2" selected original publications in cancer research are read and critically discussed. Participants are strongly advised to concurrently attend the lecture "Clinical Oncology".

In the practical course "Experimental Tumor Biology" students learn about various model systems (tissue culture and animal models) and experimental approaches in cancer research (e.g. flow cytometry, tissue staining & microscopy, quantitative expression analysis, metabolic analyses). Prior (or concurrent) attendance of the lecture "Molecular Oncology" and the "Seminars in Oncology" (1 or 2) is required.

Students work under the guidance of experienced scientists in a research laboratory on an ongoing project in cancer research.

The module allows a deeper incorporation into the research methods and techniques in the field of investigation of RNA-protein complexes in a practical course.

The module allows a deeper incorporation into the research methods and techniques in the field of protein degradation in eukaryotes in a practical course.

The module "Practical Electron Microscopy and Single Part Image Processing" consists of an electron microscopy part and an image processing part. In the electron microscopy part, the participants learn about the various elements of the electron microscope and how they work. Aspects of device alignment, focusing and data acquisition are worked out. The participants then apply different preparation methods for electron microscopy (grid preparation, negative contrast and vitrification). The samples are then imaged by electron microscopy. Subsequently, sample and data optimization is elaborated and data sets for further image processing are created.

In the image processing part, the participants are first introduced to general aspects of computer operation under Linux (basic Linux commands, basic shell scripting). Based on this, the participants determine the structure of a protein complex from a real test data set. Step by step they learn how to select good images, how to correct the data for image-dependent aberrations and how to normalize, mask and filter image data. With the prepared data the participants will determine the characteristic views of the complex (2D classification) and merge them with different methods to a DeNovo model. This model is refined in a subsequent iterative process.

In the second part of the image processing the participants apply their newly acquired knowledge to their own data and at the end of the course the participants present the various work steps and exchange experiences. The practical part of the electron microscopy practical course and the image processing part on test data is summarized in a protocol. The results on the own data are represented in the form of a scientific publication, which requires a appropriate literature work and the creation of more complex illustrations.