Seon Kinrot

1.7k total citations · 2 hit papers
5 papers, 1.0k citations indexed

About

Seon Kinrot is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Seon Kinrot has authored 5 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Molecular Biology, 2 papers in Oncology and 2 papers in Immunology. Recurrent topics in Seon Kinrot's work include CAR-T cell therapy research (2 papers), Cancer Immunotherapy and Biomarkers (2 papers) and Genomics and Chromatin Dynamics (2 papers). Seon Kinrot is often cited by papers focused on CAR-T cell therapy research (2 papers), Cancer Immunotherapy and Biomarkers (2 papers) and Genomics and Chromatin Dynamics (2 papers). Seon Kinrot collaborates with scholars based in United States, Netherlands and Spain. Seon Kinrot's co-authors include Xiaowei Zhuang, Jun-Han Su, Bogdan Bintu, Leslie J. Mateo, Nicholas A. Sinnott‐Armstrong, Kei Yamaya, Alistair N. Boettiger, Pu Zheng, Ton N. Schumacher and Ely Porter and has published in prestigious journals such as Science, Cell and Nature Biotechnology.

In The Last Decade

Seon Kinrot

5 papers receiving 995 citations

Hit Papers

Super-resolution chromatin tracing reveals domains and co... 2018 2026 2020 2023 2018 2020 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Super-resolution chromatin tracing reveals domains and cooperative interactions in single cells
    2018 636 citations Bogdan Bintu, Leslie J. Mateo et al. Science profile →
  2. Genome-Scale Imaging of the 3D Organization and Transcriptional Activity of Chromatin
    2020 346 citations Jun-Han Su, Pu Zheng et al. Cell profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Seon Kinrot United States 3 931 256 92 90 50 5 1.0k
Leslie J. Mateo United States 5 956 1.0× 294 1.1× 90 1.0× 96 1.1× 39 0.8× 5 1.0k
Chamith Y. Fonseka United States 7 542 0.6× 208 0.8× 101 1.1× 99 1.1× 26 0.5× 12 734
Kei Yamaya United States 7 749 0.8× 205 0.8× 65 0.7× 81 0.9× 22 0.4× 8 798
Daniel Smeets Germany 7 591 0.6× 110 0.4× 112 1.2× 104 1.2× 87 1.7× 7 678
Katalin Fejes Tóth Germany 7 577 0.6× 105 0.4× 36 0.4× 35 0.4× 39 0.8× 7 673
Kikuë Tachibana-Konwalski United Kingdom 10 1.1k 1.2× 318 1.2× 42 0.5× 155 1.7× 57 1.1× 11 1.3k
Iryna Pustova United States 5 631 0.7× 124 0.5× 54 0.6× 76 0.8× 44 0.9× 7 726
Katrin Küpper Germany 5 667 0.7× 213 0.8× 42 0.5× 151 1.7× 35 0.7× 5 730
Judith Miné-Hattab France 11 594 0.6× 78 0.3× 35 0.4× 50 0.6× 28 0.6× 19 637
Debbie Wei United States 13 1.1k 1.2× 339 1.3× 16 0.2× 55 0.6× 37 0.7× 16 1.2k

Countries citing papers authored by Seon Kinrot

Since Specialization
Citations

This map shows the geographic impact of Seon Kinrot's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Seon Kinrot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seon Kinrot more than expected).

Fields of papers citing papers by Seon Kinrot

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seon Kinrot. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Seon Kinrot. The network helps show where Seon Kinrot may publish in the future.

Co-authorship network of co-authors of Seon Kinrot

This figure shows the co-authorship network connecting the top 25 collaborators of Seon Kinrot. A scholar is included among the top collaborators of Seon Kinrot based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Seon Kinrot. Seon Kinrot is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

5 of 5 papers shown
1.
Zhao, Yue, Danielle Cook, Seon Kinrot, et al.. (2024). Discovery of tumor-reactive T cell receptors by massively parallel library synthesis and screening. Nature Biotechnology. 43(2). 214–222. 19 indexed citations
2.
Cook, Danielle, Andrea García-Garijo, Seon Kinrot, et al.. (2022). 406 An unbiased survey of tumor reactivity and transcriptional landscape of 1,000 clones of PD-1hi T-cells from peripheral blood during ICB treatment reveals breath and dynamics of anti-tumor immunity. Regular and Young Investigator Award Abstracts. A428–A428. 1 indexed citations
3.
Razvag, Yair, et al.. (2021). Adhering interacting cells to two opposing coverslips allows super-resolution imaging of cell-cell interfaces. Communications Biology. 4(1). 439–439. 2 indexed citations
4.
Su, Jun-Han, Pu Zheng, Seon Kinrot, Bogdan Bintu, & Xiaowei Zhuang. (2020). Genome-Scale Imaging of the 3D Organization and Transcriptional Activity of Chromatin. Cell. 182(6). 1641–1659.e26. 346 indexed citations breakdown →
5.
Bintu, Bogdan, Leslie J. Mateo, Jun-Han Su, et al.. (2018). Super-resolution chromatin tracing reveals domains and cooperative interactions in single cells. Science. 362(6413). 636 indexed citations breakdown →

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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