Motivation: Not individual single nucleotide polymorphisms (SNPs), but high-order interactions of SNPs are assumed to be responsible for complex diseases such as cancer. Therefore, one of the major goals of genetic association studies concerned with such genotype data is the identification of...

Motivation: Missing values are a common problem in genetic association studies concerned with single nucleotide polymorphisms (SNPs). Since most statistical methods cannot handle missing values, they have to be removed prior to the actual analysis. Considering only complete observations,...

Interactions of single nucleotide polymorphisms (SNPs) are assumed to be responsible for complex diseases such as sporadic breast cancer. Important goals of studies concerned with such genetic data are thus to identify combinations of SNPs that lead to a higher risk of developing a disease and...

Microarrays enable to measure the expression levels of tens of thousands of genes simultaneously. One important statistical question in such experiments is which of the several thousand genes are differentially expressed. Answering this question requires methods that can deal with multiple...

The more variables a logic expression contain, the more complicated is the interpretation of this expression. Since in a statistical sense prime implicants can be interpreted as interactions of binary variables, it is thus advantageous to convert such a logic expression into a disjunctive normal...

The issue of suitable similarity measures for a particular kind of genetic data - so called SNP data - arises, e.g., from the GENICA (The Interdisciplinary Study Group on Gene Environmental Interactions and Breast Cancer in Germany) case-control study of sporadic breast cancer. The GENICA study...