The goals of the BioLabs group are to uncover the mechanisms underlying epigenetic regulation in humans and animals and to identify the role of these mechanisms in cell differentiation and aging. We are developing novel algorithms and methods for experimental data analysis, building scalable computational pipelines and tools, and working in collaboration with biologists on various aging studies.
Longitudinal analysis of human aging
Aging is associated with processes like reduced physiological functions, increased vulnerability to diseases, chronic inflammation, and more. However, the impact of healthy aging on the molecular programming of cells is poorly understood.
In a joint research project in collaboration with Maxim Artyomov’s laboratory at Washington University in St.Louis, we aim to understand human aging on all levels, from molecular to organ-specific and organism levels, by comprehensively characterizing and performing systems analysis on high-scale multi-omics datasets. These datasets include bulk and single-cell transcriptomics, epigenomics, metabolomics, proteomics, clinical blood tests, and others. The ultimate goal is to detect major human aging drivers using well-controlled longitudinal data.
The group creates novel methods and builds computational pipelines for all stages of experimental data analysis. Our expertise in bioinformatics, machine learning, and software development allows us to combine the best practices necessary for building robust and scalable pipelines.
Major publications: