Bioinformatics and Computational Genomics

The research interests of Laboratory of Bioinformatics and Computational Genomics are focused on the application of bioinformatics and computational modelling methods in functional and structural genomics. We make use of the vast wealth of data produced by high-throughput genomics projects, such as 4DNucleome, 1000 Genomes Project, UK BioBank, Simons Genome Diversity Project, Earth BioGenome Project, ENCODE, and many others. 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 experiments (karyotyping, confocal microscopy, aCGH microarrays, short and long reads next generation sequencing), bioinformatics (protein sequence analysis, protein structure prediction), and finally biophysics (polymer theory and simulations) and various genomics data sources (DNA sequence, epigenomics, chromatin organization, topologically associating domains, three dimensional structure of chromatin identified by 3C technologies). We are presently involved in several Big Data projects both in US (4DN at Jackson Laboratory for Genomic Medicine, Earth BioGenome at University of California Davis), EU (INDEPTH, INC COST actions, ENHPATHY ITN) and in Poland (Centre of New Technologies University of Warsaw and Mathematics and Information Science Department of Warsaw  University of Technology). We perform bioinformatics and genomic analysis of 1000 Genomes Project population data for structural variants (SV) and single nucleotide polymorphism (SNP) identification in the context of 3D nuclear structure; and biophysical modeling of chromatin three-dimensional conformation within 4Dnucleome project for multiple human cell lines using HiC, HiChIP and ChIA-PET techniques. Our 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 constrains for the natural selection during the evolutionary processes, mammalian cell differentiation, and finally autoimmune diseases and cancer origin and development.