Next-generation-sequencing has become a routine approach in bioinformatics and is widely used among medical facilities around the globe. The increasing abundance of NGS data offers huge opportunities for science and personalized medicine. Nevertheless, it remains a computationally challenging task which can't be solved using classical computers. Such analysis and generation of NGS Data have to be performed using high performance computing or multiple GPUs.
I am especially interested in the scalability of Whole Genome Sequencing and Variant Calling Pipelines using GPUs and different machine learning approaches. In addition, I focus on whether associations between different types of mutations in the genome could influence the 3D folding structure of Chromatin.
I am also working on the methodological analysis of systematic bias in next-generation-sequencing platforms and different machine learning approaches for object detection and image classification of invertebrates in cooperation with Stephan Weißbach, Charlotte Hewel and Hristo Todorov.
Publications:
Sys, Stanislav J. et al. Dynamics of Associations Between Single Nucleotide Polymorphisms in Relation to Alzheimer's Disease Captured with a New Measure of Linkage Disequilibrium. Genomics and Computational Biology, [S.l.], v. 4, n. 2, p. e100045, mar. 2018. ISSN 2365-7154.