Immunosequencing Algorithms Group

Immuno-sequencing Algorithms Group

Bioinformatics · Immunogenetics · Immune repertoire profiling

Selected publications

SARS-CoV-2 epitopes are recognized by a public and diverse repertoire of human T cell receptors
Immunity 2020

Our results show that while anti-SARS-CoV-2 antibodies can distinguish convalescent patients from healthy donors, the magnitude of T-cell response was more pronounced in healthy donors sampled during COVID-19 pandemic than in donors sampled before the outbreak. This hints at the possibility that some individuals have encountered the virus but were protected by T-cell cross-reactivity observed. A public and diverse T-cell response was observed for two A*02-restricted SARS-CoV-2 epitopes, revealing a set of T-cell receptor motifs displaying germline-encoded features.

VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium
Nucleic Acids Res 2019

The increased yield of TCR specificity identification methods and the overall increase in the number of studies in the field has allowed us to expand the database more than 5-fold. Furthermore, several new analysis methods are included. For example, batch annotation of TCR repertoire sequencing samples allows for annotating large datasets on-line. Using recently developed bioinformatic methods for TCR motif mining, we have built a reduced set of high-quality TCR motifs that can be used for both training TCR specificity predictors and matching against TCRs of interest.

Exploring the pre-immune landscape of antigen-specific T cells
Genome Medicine 2018

Our results suggest that the population frequencies of specific T cells are strikingly non-uniform across epitopes that are known to elicit immune responses. This inference leads to a new definition of epitope immunogenicity based on specific TCR frequencies, which can be estimated with a high degree of accuracy in silico, thereby providing a novel framework to integrate computational and experimental genomics with basic and translational research efforts in the field of T cell immunology

VDJdb: a curated database of T-cell receptor sequences with known antigen specificity
Nucleic Acids Res 2017

The primary goal of VDJdb is to facilitate access to existing information on TCR antigen specificities, i.e. the ability to recognize known epitopes presented by known major histocompatibility complex (MHC) class I and II molecules. Our mission is to aggregate TCR specificity information on a continuous basis and establish a curated repository to store these data in the public domain

VDJtools: Unifying Post-analysis of T Cell Receptor Repertoires
PLoS Comp Biol 2015

Here we present VDJtools, a software framework that can analyze output of most commonly used TCR repertoire processing tools and allows applying a diverse set of post-analysis strategies. The main aims of our framework are: To ensure consistency of post-analysis methods and reproducibility of obtained results; to save the time of bioinformaticians analyzing TCR repertoire data by providing comprehensive tabular output and open-source API; and to provide a simple enough command line tool so that immunologists and biologists with little computational background could use it to generate publication-ready results

Towards error-free profiling of immune repertoires
Nature Methods 2014

Deep profiling of antibody and T cell–receptor repertoires by means of high-throughput sequencing has become an attractive approach for adaptive immunity studies, but its power is substantially compromised by the accumulation of PCR and sequencing errors. Here we report MIGEC (molecular identifier groups–based error correction), a strategy for high-throughput sequencing data analysis. MIGEC allows for nearly absolute error correction while fully preserving the natural diversity of complex immune repertoires

More publications:

PubMed Google Scholar

Ongoing projects

T-cell repertoire annotation

Exploring antigen specificities encoded in high-throughput T-cell receptor (TCR) sequencing data using a database of TCR sequences with known specificity. Discovering immune repertoire biomarkers using statistical approaches to TCR sequence motif inference. Linking specific TCR repertoire structure to the immunogenicity of cognate antigens.


In-silico modeling of TCR:peptide:MHC complex structures. Linking structural data and the organization of T-cell repertoire: CD4/CD8 T-cell differentiation and αβ chain pairing. Building statistical models of TCR:pMHC contacts with an ultimate goal of developing an efficient method for TCR:pMHC binding prediction.

Antibodyome analysis

Developing fast algorithms for antibody lineage tree inference and somatic hypermutation analysis. Implementing novel approaches to high-througput antibody sequencing data analysis that focus on the clonal architecture instead of individual sequences/clonotypes. Exploring differences between B-cell subsets, B-cell memory and the structure of B-cell repertoire in cancer patients.

Epitope immunogenicity

Ranking foreign and self peptides based on their predicted ability to elicit immune response. Searching for physicochemical characteristics and similarities to self and viral peptidomes that are exploited by the adaptive immune system to act as an efficients self-vs-nonself classifier. Developing bioinformatic tools for selection of optimal neoantigen targets for cancer immunotherapy.

Studying T- and B-cell responses in COVID-19

Currently, we are assaying thousands of immune repertoire sequencing datasets coming from convalescent donors, donors that had a history of COVID infection and healthy donors to discover biomarkers that are associated with immunity to COVID-19. We aim at discovering immunogenic SARS-CoV-2 epitopes, as well as T-cell receptor sequences that recognize them. We also study antibody evolution and affinity of various antibodies to distinct SARS-CoV-2 proteins.

Software, databases, tutorials

Members & Alumni

Mikhail /Mike/ Shugay, Ph.D

Principal Investigator

Dmitry Shcherbinin, Ph.D


Vadim Karnaukhov, M.Sc

Ph.D student, co-supervised with Dr. Ivan Zvyagin (Skoltech)

Anastasiya Pivnuk

M.Sc student (Skoltech)

Dmitry Bagaev

Former M.Sc student, now at Eindhoven University of Technology (Eindhoven, The Netherlands)

Anna Obraztsova

Former M.Sc student, now at German Cancer Research Center (Heidelberg, Germany)

Alla Fedorova

Former M.Sc student

Anna Koneva

Former Research Scientist (IBCH RAS)

Alexey Eliseev

Former M.Sc student, now at BostonGene LLC (Waltham, MA, USA)

Vlad Belousov

Former M.Sc student, now at BostonGene LLC (Waltham, MA, USA)

Vasily Tsvetkov

Former M.Sc student, now at Immunomind LLC (CA, USA)

Mikhail Ignatov

Former M.Sc student, now at Stony Brook University (New York, USA)


Pirogov Russian Medical State University / Institute of Bioorganic Chemistry RAS

Moscow, Russia

  • Prof. Dmitry Chudakov
  • Dr. Ivan Zvyagin
  • Dr. Olga Britanova

National Research Center for Hematology

Moscow, Russia

  • Dr. Grigory Efimov

Skolkovo Institute of Science and Technology

Moscow Oblast, Russia

  • Prof. Georgy Bazykin

Cardiff University

Cardiff, United Kingdom

  • Prof. Andrew Sewell
  • Prof. David Price

University of New South Wales

Sydney, Australia

  • Prof. Fabio Luciani

Sorbonne University

Paris, France

  • Prof. David Klatzmann
  • Prof. Encarnita Mariotti-Ferrandiz

University of Gothenburg

Gothenburg, Sweden

  • Prof. Ola Grimsholm

University of Oxford

Oxford, UK

  • Prof. Hashem Koohy
  • Prof. Persephone Borrow