Research group

BioLabs

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.

Research projects

  • Epigenetic changes in aging human monocytes – a joint research project dedicated to the study of healthy human aging in collaboration with Maxim Artyomov’s laboratory at Washington University in St. Louis. The group creates bioinformatics pipelines and develops novel algorithms and methods for epigenetic data analysis.
  • Immune system aging – this project studies the aging of the immune system in mice and humans, applying single-cell methods for comprehensive characterizing of cell populations development.
  • Longitudinal analysis of healthy human aging – the project involves the study of healthy human aging, aiming to find major aging drivers from longitudinal multi-omics data.

Tools

  • SPAN Peak Analyzer – is 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.
  • JBR Genome Browser – is 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.
  • SnakeCharm – the Snakemake workflow management system support plugin for IntelliJ Platform IDEs, adds syntax highlighting, code completion, on-the-fly code verifications, and advanced integration with the Snakemake ecosystem.
  • Pubtrends – is a scientific publication exploratory tool capable of analyzing the intellectual structure of a research field or similar papers analysis. We apply the bibliometrics method for citation information and natural language processing algorithms for text analysis. The service allows users to find the most cited papers, explore topics, visualize citations and paper similarity graphs, and generate automated literature reviews.

Source code

All the source code is available on GitHub.

Student Internship

Group Members

Oleg Shpynov
Head of Research Lab/Group
Roman Cherniatchik
Researcher
Aleksei Dievskii
Researcher
Petr Tsurinov
Researcher