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.
- Epigenetic changes in aging human monocytes – joint research project dedicated to studying 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 - project, which studies immune system aging in mice and humans, applying single cell methods for comprehensive characterizing of cell populations development.
- Longitudinal analysis of healthy human aging - study of healthy human aging, aiming to find major aging drivers from longitudinal multiomics data.
A full list of projects is available here.
- 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 of view-ing large sessions, semi-supervised peak and annotation functionality that is integrated with SPAN peak caller.
- SnakeCharm – 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 – is a scientific publications exploratory tool capable of analysing intellectual structure of research field or similar papers analysis. We apply bibliometrics method for citations information and natural language processing algorithms for text analysis. Service allows to find most cited papers, explore topics, visualize citations and paper similary graphs, and generate automated literature reviews.
All the source code is available on GitHub.
Various presentations including journal club and talks are here.
- 2020, Simon Tsirikov and Artem Davletov, SnakeCharm plugin Code Analysis Improvements
- 2020, Anna Nikiforovskay, Bachelor Thesis "Extractive summarization for biomedical papers"
- 2019, Anna Vlasova, "Review generation for publications analysis service"
- 2019, Daria Chaplygina, "Noisy peak calling 2"
- 2019, Daria Likholetova and Nina Lukashina, "ARM using Fishbone diagram"
- 2019, Anna Vlasova and Nikolai Kapralov, "Publications analysis"
- 2019, Daria Sharkova and Nikita Nazarov, "Snakecharm plugin"
- 2019, Elena Kartysheva, "SPAN model improvement"
- 2019, Vladislav Kalinin, Master Thesis "Web server for accessing to human Chip-Seq data hosted in GEO and Chip-Atlas"
- 2019, Darya Sharkova, "SnakeCharm plugin code insight improvement"
- 2019, Alexander Petrovsky, Dmitry Belikov, "Detection of unique shared genomic sequences for the given group of organisms"
- 2019, Elena Kartysheva, "Improving SPAN data model with generalised linear regression"
- 2019, Daria Likholetova, Nina Lukashina, "Association Rule Mining on genome regions using fishbone diagrams"
- 2019, Daria Chaplygina, "Noisy peak calling"
- 2019, Daria Balashova, "ChIPSeq Rescue failures with Neural Networks"
- 2018, Nikolai Kapralov, "Publications analysis service"
- 2017, Eugene Bakin, “ChipQuery - Chipseq data comparison”
- 2016, Sergey Chernov, "A comprehensive comparison of tools for differential ChIP-seq analysis"
- 2016, Dmitriy Groshev, “Comparing the bisulphite sequencing data”
- 2015, Anna Atamanova, “Generalising data on bins for randomly sized genomic loci"
- 2014, Sergei Lebedev, Master Thesis “Bisulphite sequencing data modeling”
- 2013, Alexey Dievsky, Master Thesis “Modeling difference in ChIP-seq data”
- Single Cell Sequencing School 2020
- Epigenetics data computational analysis
- Publications what-where-when
Source is available on GitHub