Dariusz Plewczynski's interests are focused on functional and structural genomics. His functional attempts make use of the vast wealth of data produced by high-throughput genomics projects. The major tools that are used in this interdisciplinary research endeavor include statistical data analysis (GWAS studies, clustering, machine learning), genomic variation analysis using diverse data sources (karyotyping, confocal microscopy, aCGH microarrays, next generation sequencing), bioinformatics (protein sequence analysis, protein structure prediction), and finally biophysics (polymer theory and simulations) and genomics (epigenetics, genome domains, three dimensional structure of chromatin). His goal is to combine SV, epigenomic, transcriptional and super-resolution imaging data with spatial and temporal nucleus structure for better understanding of the biological function of genomes, the genomic structural variation within populations of cells and between individuals from different species, the spatial constraints for the natural selection during the evolutionary processes, mammalian cell differentiation, and finally cancer and autoimmune diseases origin and development.