Development of new experimental approaches and computational tools for the analysis of single-cell sequencing data

Computational work in our lab focuses on developing new algorithms and scalable tools for analysis of massive single-cell datasets originated from wet lab and their integration across platforms and techniques. In particular, we are interested in creating new approaches for comprehensive inference of developmental trajectories and delineation of cell atlases from single-cell data, understanding the role of cell-to-cell signaling and biological pathways in lineage commitment and transitions between cellular states. We explore novel methods for multidimensional and multimodal data visualization to get comprehensive topography of the cellular landscapes. Single-cell multiomics sequencing will allow us to dissect the complex ecosystem of the tumour, the immune repertoire infiltrating it, and to understand the intercellular communication between immune subpopulations of cells. It will also provide new mechanistic insight into biology of cancer including uveal melanoma and point at the potential therapies.