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.
A semi-supervised multipurpose peak caller capable of processing a broad range of ChIP-seq, ATAC-seq, and single-cell ATAC-seq datasets that robustly handles multiple replicates and noise by leveraging limited manual annotation information.
A fast and reliable next-generation genome browser with enhanced capabilities for viewing large sessions, semi-supervised peak, and annotation functionality. It is integrated with the SPAN Peak Analyzer.
A snakemake workflow management system support plugin for IntelliJ Platform IDEs, adding syntax highlighting, code completion, on-the-fly code verifications and advanced integration with snakemake ecosystem.
A scientific publications exploratory tool capable of analysing intellectual structure of a research field or performing analysis of similar papers. We apply bibliometrics methods to citations graphs and natural language processing algorithms to text analysis. The service allows to find most cited papers, explore topics, visualize citations and paper similarity graphs, and generate automated literature reviews.
A hybrid data mining algorithm for exploring hidden dependencies in observational datasets. It combines Associated Rules Learning technique and Information Theory for automated building of the Ishikawa diagram – a visualization method for complex patterns and rules in data.