Ryan Bjordahl

1.6k total citations
51 papers, 747 citations indexed

About

Ryan Bjordahl is a scholar working on Oncology, Immunology and Molecular Biology. According to data from OpenAlex, Ryan Bjordahl has authored 51 papers receiving a total of 747 indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Oncology, 38 papers in Immunology and 18 papers in Molecular Biology. Recurrent topics in Ryan Bjordahl's work include CAR-T cell therapy research (46 papers), Immune Cell Function and Interaction (36 papers) and CRISPR and Genetic Engineering (9 papers). Ryan Bjordahl is often cited by papers focused on CAR-T cell therapy research (46 papers), Immune Cell Function and Interaction (36 papers) and CRISPR and Genetic Engineering (9 papers). Ryan Bjordahl collaborates with scholars based in United States, Sweden and Norway. Ryan Bjordahl's co-authors include Bahram Valamehr, Jeffrey S. Miller, Svetlana Gaidarova, Bruce Walcheck, Robert Blum, Dan S. Kaufman, Ramzey Abujarour, Zhu Huang, Paul Rogers and Jianming Wu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Blood and The Journal of Immunology.

In The Last Decade

Ryan Bjordahl

50 papers receiving 736 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ryan Bjordahl United States 13 559 510 197 66 66 51 747
Ashley Knights Australia 13 498 0.9× 322 0.6× 269 1.4× 47 0.7× 34 0.5× 15 705
Antonio Valeri Spain 12 303 0.5× 294 0.6× 124 0.6× 96 1.5× 60 0.9× 23 462
Maxime Dhainaut United States 7 436 0.8× 335 0.7× 240 1.2× 14 0.2× 43 0.7× 12 707
Trina J. Stewart United States 16 575 1.0× 466 0.9× 181 0.9× 17 0.3× 88 1.3× 20 824
Diana Campillo-Davó Belgium 14 309 0.6× 377 0.7× 248 1.3× 90 1.4× 89 1.3× 25 617
Gina Scurti United States 11 323 0.6× 281 0.6× 182 0.9× 13 0.2× 51 0.8× 23 539
Edison Y. Chiu United States 6 459 0.8× 475 0.9× 136 0.7× 21 0.3× 50 0.8× 8 641
Marie‐Christine Pandolfino France 16 632 1.1× 488 1.0× 155 0.8× 14 0.2× 96 1.5× 29 753
Julia Piasecki United States 7 142 0.3× 260 0.5× 232 1.2× 64 1.0× 87 1.3× 22 403
Heinke Conrad Germany 12 238 0.4× 269 0.5× 150 0.8× 24 0.4× 47 0.7× 16 460

Countries citing papers authored by Ryan Bjordahl

Since Specialization
Citations

This map shows the geographic impact of Ryan Bjordahl'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 Ryan Bjordahl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryan Bjordahl more than expected).

Fields of papers citing papers by Ryan Bjordahl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryan Bjordahl. 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 Ryan Bjordahl. The network helps show where Ryan Bjordahl may publish in the future.

Co-authorship network of co-authors of Ryan Bjordahl

This figure shows the co-authorship network connecting the top 25 collaborators of Ryan Bjordahl. A scholar is included among the top collaborators of Ryan Bjordahl 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 Ryan Bjordahl. Ryan Bjordahl is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Yang, Bi-Huei, Angela Liao, Mochtar Pribadi, et al.. (2025). iPSC-derived trimodal T cells engineered with CAR, TCR, and hnCD16 modalities can overcome antigen escape in heterogeneous tumors. Cell Reports Medicine. 6(7). 102195–102195.
2.
Bulliard, Yannick, et al.. (2024). From promise to practice: CAR T and Treg cell therapies in autoimmunity and other immune-mediated diseases. Frontiers in Immunology. 15. 1509956–1509956. 12 indexed citations
4.
Snyder, Kristin M., Zachary Davis, Bryan Hancock, et al.. (2024). iPSC-derived NK cells expressing high-affinity IgG Fc receptor fusion CD64/16A to mediate flexible, multi-tumor antigen targeting for lymphoma. Frontiers in Immunology. 15. 1407567–1407567. 3 indexed citations
5.
Snyder, Kristin M., Zachary Davis, Martin Hosking, et al.. (2023). iPSC-derived natural killer cells expressing the FcγR fusion CD64/16A can be armed with antibodies for multitumor antigen targeting. Journal for ImmunoTherapy of Cancer. 11(12). e007280–e007280. 13 indexed citations
6.
Ning, Jianfang, Frank Cichocki, Hongbo Wang, et al.. (2023). 372 IPSC-Derived NK cells Exhibit Potent In Vitro and In Vivo Tumorcidal Activity Against Patient-Derived Glioblastoma Stem Cells (GSCs). Neurosurgery. 69(Supplement_1). 64–64. 1 indexed citations
7.
Gutierrez, Martin, Melissa Johnson, David Sommerhalder, et al.. (2022). 727 Interim phase I clinical data of FT538, an off-the-shelf, multiplexed-engineered, iPSC-derived NK cell therapy, combined with monoclonal antibodies in patients with advanced solid tumors. Regular and Young Investigator Award Abstracts. A760–A760. 1 indexed citations
8.
Drake, Charles G., Alex Garcia, Chia‐Wei Chang, et al.. (2022). 326 Off-the-shelf iPSC-derived CAR-T cells targeting KLK2 demonstrate prolonged tumor control and survival in xenograft models of prostate cancer. Regular and Young Investigator Award Abstracts. A343–A343. 2 indexed citations
9.
Mahmood, Sajid, Yijia Pan, Bryan Hancock, et al.. (2021). Dual Chimeric Antigen Receptor Approach Combining Novel Tumor Targeting Strategies Circumvents Antigen Escape in Multiple Myeloma. Blood. 138(Supplement 1). 1718–1718. 9 indexed citations
10.
Mbofung, Rina M., Yijia Pan, Brian Groff, et al.. (2021). Off-the-Shelf, iPSC-Derived CAR-NK Cells Multiplexed-Engineered for the Avoidance of Allogeneic Host Immune Cell Rejection. Blood. 138(Supplement 1). 2795–2795. 2 indexed citations
11.
Chiu, Emily, Martin Felices, Frank Cichocki, et al.. (2021). Anti-NKG2C/IL-15/anti-CD33 killer engager directs primary and iPSC-derived NKG2C+ NK cells to target myeloid leukemia. Molecular Therapy. 29(12). 3410–3421. 35 indexed citations
12.
Pan, Yijia, Brian Groff, Rina M. Mbofung, et al.. (2021). A Novel Stealth Strategy That Activates Adoptively Transferred Allogeneic Immune Cells and Avoids Rejection for Off-the-Shelf Cell-Based Cancer Therapy. Blood. 138(Supplement 1). 4800–4800. 1 indexed citations
14.
Bjordahl, Ryan, John Goulding, Mochtar Pribadi, et al.. (2020). Development of a Novel MICA/B-Specific CAR As a Pan-Tumor Targeting Strategy for Off-the-Shelf, Cell-Based Cancer Immunotherapy. Blood. 136(Supplement 1). 5–6. 2 indexed citations
16.
17.
Bjordahl, Ryan, Raedun Clarke, Svetlana Gaidarova, et al.. (2017). Multi-Functional Genetic Engineering of Pluripotent Cell Lines for Universal Off-the-Shelf Natural Killer Cell Cancer Immunotherapy. Blood. 130. 3187–3187. 1 indexed citations
18.
Bjordahl, Ryan, Christian Steidl, Randy D. Gascoyne, & Carl F. Ware. (2013). Lymphotoxin network pathways shape the tumor microenvironment. Current Opinion in Immunology. 25(2). 222–229. 26 indexed citations
19.
Bjordahl, Ryan, Laurent Gapin, Philippa Marrack, & Yosef Refaeli. (2012). iNKT Cells Suppress the CD8+ T Cell Response to a Murine Burkitt’s-Like B Cell Lymphoma. PLoS ONE. 7(8). e42635–e42635. 22 indexed citations
20.
Humann, Jessica, et al.. (2007). Expression of the p60 Autolysin Enhances NK Cell Activation and Is Required for Listeria monocytogenes Expansion in IFN-γ-Responsive Mice. The Journal of Immunology. 178(4). 2407–2414. 43 indexed citations

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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