Research
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 Objectives
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.
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. The ultimate goal is to detect major human aging drivers using well-controlled longitudinal data by analyzing bulk and single-cell transcriptomics, epigenomics, proteomics, clinical blood tests and others.
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, required for producing reproducible biological insights.
We are working together with the Aging Biology Foundation and collaborating with:
- The Artyomov Lab, Department of Pathology & Immunology, Washington University School of Medicine
- Centre for Human and Applied Physiological Sciences, King’s College London
- and others
Competence Areas (Computational)
- Epigenetics – DNA methylation, ChIP-seq, ATAC-seq, and related assays.
- Transcriptomics – RNA-seq and advanced gene expression analyses.
- Single-Cell & Cytometry – flow cytometry, Cytek, CyTOF data processing.
- Multi-Omics – metabolomics, proteomics, Somascan, and integrative approaches.
Technical Expertise
- Scalable Computational Pipelines – design and implementation (e.g., Snakemake, Nextflow).
- Big Data Processing & Visualization – interactive and high-performance tools for exploration.
- Statistical Analysis – hypothesis testing, multiple comparison corrections, advanced modeling.
- Software Development - proficiency in Java/Kotlin, Python, R
- Machine Learning – predictive modeling, pattern recognition, and biological insight discovery.
Software Projects
Omnipeak
A universal HMM-based peak caller capable of processing a broad range of ChIP-seq, ATAC-seq, and single-cell ATAC-seq datasets of different quality.
JBR Genome Browser
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
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.
Pubtrends
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.
Group Members
Researcher