Genetic variation in combination with epidemiological factors can lead to the development of complex diseases such as cancer. The SFB 475 project "Statistical Complexity Reduction in Molecular Epidemiology" is concerned with finding such risk factors, with the main focus of attention on gene-gene and gene-environment-interactions.
Contact: Prof. Dr. Katja Ickstadt
Gene Expression Data
Micro-arrays make the simulaneous measurement of tens of thousands of genes possible. Not just this huge number of variables combined with a much lower number of observations, but also the very noisy signals some micro-arrays deliver present large problems for the analysis of such data, which can only be negotiated through interdisciplinary collaboration. One such collaboration takes place in the SFB 475 project "Statistical Complexity Reduction in Molecular Epidemiology".
Proteins are responsible for almost every biological process in an organism and even for the development of diseases like cancer. This is why the research of the proteome and also particularly the indentifcation of proteins, whose expression differs between different groups (e.g. diseased and healthy tissue), and the location of protein-protein interaction, is of great interest. Again, the interdiciplinary collaberation is of great use, like it takes place in the Centre for Applied Proteomics.
Controlled Clinical Trials
In controlled clinical trials a treatment will be evaluated against another. The department "Statistics with Application in the Field of Engineering Sciences" is concerned with Meta-Analysis of combinations of such controlled clinical trials and the planning and evaluation of such studies with flexible or adaptable designs.
Contact: PD Dr. Guido Knapp
Statistical methods are necessary for the planning and evaluation of toxicological studies, in order to be able to analyse the possible harmful effects of substances. The department "Mathematical Statistcs with Applications in Biometrics" is working together with the Leibniz Research Centre for Working Environment and Human Factors to analsye such studies. A big problem, which has been observed by the "Mathematical Statistics and Applications in Science" is the tansferrability of animal testing to how a substance will affect humans.
The risk of getting a disease can also be dependent on the area in which you live. Spatial statistics and geographical information is recorded in order to discover and categorise such diseases.