Personal Websites

Scientific record: Google Scholar

Open-source software contributions: GitHub

Twitter: @antigenomics

Forums: BioStars, RepSeq community forum

Mikhail Shugay

Mikhail graduated from the Faculty of Physics, Moscow State University in 2011 and received his PhD from the Department of Genetics, University of Navarra, Spain in 2013. His early research was devoted to bioinformatic analysis of fusion genes in cancer. After moving back to Moscow, he joined the Genomics of Adaptive Immunity group led by Prof. Dmitry Chudakov. Mikhail has been involved in a number of pioneering projects aimed at developing a technology to profile human adaptive immune system using next-generation sequencing and advanced molecular biology techniques. Additionally, Mikhail has developed methods for high-fidelity sequencing and rare mutation detection as an affiliate of Pirogov Russian National Research Medical University. Mikhail is a regular visiting scholar of the Adaptive Immunity Group at Central European Institute of Technology, Czech Republic, he is also involved in software development at Skolkovo resident company Milaboratory LLC.

Mikhail’s research interests include bioinformatics for high throughput sequencing, systems immunology and cancer immunotherapy. He has been invited as a speaker to a number of major events in the immune repertoire profiling community that took place in Portugal, France, USA, The Netherlands and Switzerland. Mikhail has authored and co-authored 25 research papers during the last 5 years of his work.

At Skoltech, Mikhail works on bioinformatic analysis of large-scale T- and B-cell receptor repertoire sequencing data to gain new insights into the structure and dynamics of the adaptive immune system in health and disease.

Professor: Dmitry Chudakov

  • Bioinformatic analysis of large-scale T- and B-cell receptor repertoire sequencing data.
  • Systems biology of adaptive immunity in health and disease.

Selected publications:

  • Shagin DA, Shagina IA, Zaretsky AR, Barsova EV, Kelmanson IV, Lukyanov S, Chudakov DM,
    Shugay M. ​ A high-throughput assay for quantitative measurement of PCR errors. ​ Scientific
    Reports​ 2017; 7:2718 doi:10.1038/s41598-017-02727-8
  • Shugay M​ , Zaretsky AR, Shagin DA, Shagina IA, Volchenkov IA, Shelenkov AA, Lebedin MY,
    Bagaev DV, Lukyanov S, Chudakov DM. MAGERI: Computational pipeline for
    molecular-barcoded targeted resequencing. ​ PLoS Comp Biol​ 2017; 13(5):e1005480
  • Turchaninova MA, Davydov A, Britanova OV, ​ Shugay M , Bikos V, Merzlyak EM, Staroverov
    DB, Bolotin DA, Kirgizova VI, Mamedov IZ, Izraelson M, Logacheva MD, Plevova K,
    Pospisilova S, Chudakov DM.​ ​ High quality full length immunoglobulin profiling with unique
    molecular barcoding. ​ Nature Protocols​ 2016; 11 (9), 1599-1616
  • Britanova OV, ​ Shugay M, Merzlyak EM, Staroverov DB, Putintseva EV, Turchaninova MA,
    Mamedov IZ, Bolotin DA, Izraelson M, Davydov A, Rebrikov DV, Lukyanov S, Chudakov M.
    Dynamics of individual T cell repertoires: From cord blood to centenarians. ​ J Immunol​ 2016; 196
    (12), 5005-5013
  • Shugay M​ , Bagaev DV, Turchaninova MA, Bolotin DA, Putintseva EV, Pogorelyy MV, Nazarov
    VI, Zvyagin IV, Kirgizov KI, Skorobogatova EV, Chudakov DM. VDJtools: unifying
    post-analysis of T cell receptor repertoires. ​ PLoS Comp Biol​ 2015 Nov; 11(11):e1004503.
  • Feng Y, van der Veeken J, ​ Shugay M​ , Putintseva EV, Osmanbeyoglu HU, Dikiy S, Hoyos BE,
    Moltedo B, Hemmers S, Treuting P, Leslie CS, Chudakov DM, Rudensky AY. A mechanism for
    expansion of the regulatory T cell repertoire and its role in enforcing self-tolerance. ​ Nature 2015;
  • Shugay M​ , Britanova OV, Merzlyak EM, Turchaninova MA, Mamedov IZ, Tuganbaev TR,
    Bolotin DA, Staroverov DB, Putintseva EV, Plevova K, Linnemann C, Shagin D, Pospisilova S,
    Lukyanov S, Schumacher TN, Chudakov DM. Towards error-free profiling of immune
    repertoires. ​ Nature Methods​ , 2014 June 1, doi:10.1038/nmeth.2960.
  • Bolotin DA, Shugay M , Mamedov IZ, Putintseva EV, Turchaninova MA, Zvyagin IV,
    Britanova OV, Chudakov DM. MiTCR: software for T-cell receptor sequencing data analysis.
    Nature Methods​ 2013 Aug;10(9):813-4.
  • Shugay M​ , Ortiz de Mendíbil I, Vizmanos JL, Novo FJ. Oncofuse: a computational framework
    for the prediction of the oncogenic potential of gene fusions. ​ Bioinformatics​ 2013 Aug 24.
  • M.Sc in Biochemical Physics, Moscow State University, Moscow, Russia (2011)
  • Ph.D. thesis “Computational Analysis of Fusion Genes in Cancer”, Universidad de Navarra, Pamplona, Spain (2013)
  • Bioinformatics:​ algorithms and software development for next-generation sequencing (NGS)
    data analysis
  • Cancer research:​ data mining for cancer research, rare mutation detection with NGS
  • Immunology:​ cancer immunotherapy, analysis of immunome structure and diversity using deep
    sequencing, functional annotation of T-cell receptor repertoires