Исследовательская группа


The goal of BioLabs is to uncover fundamental epigenetic regulation mechanisms and to identify their role in cell differentiation and aging in humans and other animals.

Aging project

Joint project with Max Artyomov Lab at Washington University in St. Louis dedicated to analysis of age related changes in human blood monocytes during healthy aging.

Epigenome analysis tools

A number of tools for analyzing epigenetic data were developed at the Labs. They allow us to compare and characterize different data sets: ChIP-seq, BS-seq, and (via integrated kallisto and Cufflinks) – RNA-seq. A single pipeline combining those tools is available as a standalone JAR.


CMeth is a tool for analyzing and comparing replicated whole-genome bisulfite sequencing data. Detailed description and examples are available on GitHub.


Zero Inflated Negative Binomial Restricted Algorithm is a tool for analyzing and comparing replicated ChIP-seq data. Description is available on GitHub.

Genome Browser

Most genome browsers, such as UCSC Genome Browser, JBrowse, IGV, WashU, were designed without extensibility in mind. As a result it's difficult or impossible to customize them. We've addressed the issue by developing a browser of our own.

Feature highlights:

  • Front-end agnostic. The browser can be used on the desktop or web service.
  • Integrated support for common track formats, e.g. WIG, BED.
  • Integrated support for blending and combining tracks.
  • Easy visualization of multiple genomic loci.

Rule mining

Apart from probabilistic models, we've developed a unified approach to data analysis in terms of predicates with deep knowledge of domain. This way epigenetic changes can be dealt with in terms of logical expressions over histone modifications, methylation and transcription data.



Студенческая практика

Several student projects were finished at BioLabs:

  • Sergey Chernov, "A comprehensive comparison of tools for differential ChIP-seq analysis"
  • Dmitriy Groshev, “Comparing the bisulphite sequencing data”
  • Anna Atamanova, “Generalizing data on bins for randomly sized genomic loci"

The interns are welcome to pursue one of these topics:

  • Epigenetic data modeling
  • Causal networks and rule mining in relation to epigenomic data
  • Epigenetic data analysis tools, browsers etc.

Two members of BioLabs defended their master's theses:

If you are interested in doing an internship or working on your thesis with the Labs, please contact us.