Karin Schwarzbauer

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Quantitative analyses of next-generation sequencing (NGS) data, such as the detection of copy number variations (CNVs), remain challenging. Current methods detect CNVs as changes in the depth of coverage along chromosomes. Technological or genomic variations in the depth of coverage thus lead to a high false discovery rate (FDR), even upon correction for GC(More)
This paper demonstrates that several known sequence kernels can be expressed in a unified framework in which the position specificity is modeled by fuzzy equivalence relations. In addition to this interpretation, we address the practical issues of positive semidefiniteness, computational complexity, and the extraction of interpretable features from the(More)
To gain deeper insights into principles of cell biology, it is essential to understand how cells reorganize their genomes by chromatin remodeling. We analyzed chromatin remodeling on next generation sequencing data from resting and activated T cells to determine a whole-genome chromatin remodeling landscape. We consider chromatin remodeling in terms of(More)
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