Yuri Pritykin

Yuri Pritykin

Assistant Professor

Princeton University

I am an Assistant Professor in the Lewis-Sigler Institute for Integrative Genomics and the Computer Science Department at Princeton University (starting January 2021).

My main interest and expertise are in using applied statistics, machine learning, and efficient algorithms to address fundamental problems in biology and medicine by integrative analysis of multi-dimensional data.

Previously I was a postdoctoral researcher in the Leslie lab in Computational and Systems Biology Program at Memorial Sloan Kettering Cancer Center. I received PhD in computer science from Princeton University advised by Mona Singh and MSc and PhD in mathematics from Lomonosov Moscow State University advised by Alexei Semenov and Andrej Muchnik. I finished Moscow School 57.

Positions

Positions for computational biologists are available at multiple levels in my lab, details and the lab website coming soon. Prospective PhD students interested in working with me are encouraged to apply to QCB and CS graduate programs at Princeton. Current Princeton students interested in working with me are encouraged to contact me directly.

Awards

  • AACR-Bristol-Myers Squibb Immuno-oncology Research Fellowship (2019)
  • Memorial Sloan Kettering-Parker Institute for Cancer Immunotherapy-Cycle for Survival Fund (2018)

Interests

  • Computational biology
  • Cancer immunology
  • Regulation of gene expression
  • Functional genomics
  • Single-cell technologies

Education

  • PhD, Computer Science, 2014

    Princeton University

  • Candidate of Sc (PhD), Mathematics, 2009

    Lomonosov Moscow State University

  • Specialist (MSc), Mathematics, 2007

    Lomonosov Moscow State University

Research

We develop computational methods for design and analysis of high-throughput functional genomic assays and perturbations, with a focus on multi-modal single-cell technologies. We apply these methods to study regulatory genomics of cell function and cell-cell interactions in vivo in close collaboration with experimental biologists, with a focus on immunology and cancer.

Examples of our past and ongoing work are below.


CD8 T cells form the central component of adaptive immune system and are essential in defense against viral and bacterial infections and in tumor immunity. Better molecular characterization of CD8 T cells in different contexts is fundamentally important and can lead to improved clinical results in cancer immunotherapies, infectious diseases, autoimmunity. We performed an extensive genomic, single-cell, and transcription factor analysis of CD8 T cell functional and dysfunctional states. We now continue studying regulatory mechanisms and cell-cell interactions governing CD8 T cell activation and functional commitment across immune challenges using single-cell multi-omics.


Programmable genome editing using CRISPR has tremendously advanced life sciences. To facilitate the use of this technology, especially in the noncoding genome and for batch screens, we developed GuideScan, a fully customizable CRISPR guide RNA design tool. We now continue working on tools for design and analysis of CRISPR-based genome perturbations and their combinations with single-cell functional genomic assays.


Regulatory T (Treg) cells are critical for tolerance to self-antigens and preventing autoimmunity. Their differentiation and function are controlled by transcription factor Foxp3, but mechanistic understanding of Foxp3 role remains elusive. Using functional genomic analysis, we explored Foxp3 function and its interaction with a highly expressed closely related factor Foxp1. We are now studying the role of Foxp3 and other factors in organizing chromatin architecture of Treg cells.


Cross-linking immunoprecipitation followed by sequencing (CLIP-seq) is a family of methods for profiling sites of protein binding to RNA. In particular, CLIP has been used to identify targets of microRNAs, small non-coding RNA molecules that, when bound to a protein Ago2, regulate gene expression post-transcriptionally. We developed a new algorithm CLIPanalyze for analysis of such data and used it for comprehensive analysis of microRNA targets in vivo in mouse embryonic stem cells, developing embryos, adult tissues and multiple cancer models.

Publications

(2019). Transcriptional basis of mouse and human dendritic cell heterogeneity. Cell.

PDF DOI

(2018). Epigenetic control of innate and adaptive immune memory. Nature Immunology.

DOI rdcu

Contact

  • pritykin at princeton.edu
  • 245 Carl Icahn Lab, Lewis-Sigler Institute for Integrative Genomics, South Drive, Princeton University, Princeton, NJ 08544