Yasuko Tada

1.8k total citations · 1 hit paper
8 papers, 1.2k citations indexed

About

Yasuko Tada is a scholar working on Oncology, Immunology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Yasuko Tada has authored 8 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Oncology, 4 papers in Immunology and 2 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Yasuko Tada's work include Cancer Immunotherapy and Biomarkers (7 papers), CAR-T cell therapy research (4 papers) and Immune Cell Function and Interaction (2 papers). Yasuko Tada is often cited by papers focused on Cancer Immunotherapy and Biomarkers (7 papers), CAR-T cell therapy research (4 papers) and Immune Cell Function and Interaction (2 papers). Yasuko Tada collaborates with scholars based in Japan, United States and United Kingdom. Yasuko Tada's co-authors include Hiroyoshi Nishikawa, Yosuke Togashi, Kohei Shitara, Akihito Kawazoe, Eiichi Sato, Shota Fukuoka, Akinori Sasaki, Takahiro Kamada, Yoshiaki Nakamura and Christopher Tay and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and International Immunology.

In The Last Decade

Yasuko Tada

8 papers receiving 1.1k citations

Hit Papers

PD-1 + regulatory T cells amplified by PD-1 blockade prom... 2019 2026 2021 2023 2019 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yasuko Tada Japan 6 877 691 270 167 103 8 1.2k
Akihiro Hosoi Japan 16 568 0.6× 592 0.9× 158 0.6× 236 1.4× 95 0.9× 30 928
Federico Sandoval France 9 777 0.9× 594 0.9× 179 0.7× 306 1.8× 147 1.4× 16 1.1k
Y Ino Japan 8 824 0.9× 584 0.8× 189 0.7× 330 2.0× 164 1.6× 8 1.2k
Darryl A. Oble United States 12 733 0.8× 656 0.9× 133 0.5× 153 0.9× 37 0.4× 15 1.1k
Gulidanna Shayan United States 10 771 0.9× 808 1.2× 120 0.4× 218 1.3× 109 1.1× 20 1.2k
Inge Lodewijckx Belgium 5 425 0.5× 291 0.4× 132 0.5× 273 1.6× 119 1.2× 7 738
W.E. Gillanders United States 5 826 0.9× 493 0.7× 145 0.5× 231 1.4× 133 1.3× 6 1.0k
Chuanyong Mu China 12 761 0.9× 375 0.5× 352 1.3× 155 0.9× 114 1.1× 24 964
Sara Solt United States 8 1.6k 1.8× 1.2k 1.8× 128 0.5× 288 1.7× 144 1.4× 9 1.9k
Masato Sugano Japan 13 427 0.5× 135 0.2× 236 0.9× 181 1.1× 117 1.1× 44 709

Countries citing papers authored by Yasuko Tada

Since Specialization
Citations

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

Fields of papers citing papers by Yasuko Tada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yasuko Tada

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

All Works

8 of 8 papers shown
1.
Mori, Shigeyuki, Daisuke Sugiyama, Yasuhiro Kojima, et al.. (2021). Cancer immunotherapy with PI3K and PD-1 dual-blockade via optimal modulation of T cell activation signal. Journal for ImmunoTherapy of Cancer. 9(8). e002279–e002279. 35 indexed citations
2.
Sugiyama, Eri, Yosuke Togashi, Yoshiko Takeuchi, et al.. (2020). Blockade of EGFR improves responsiveness to PD-1 blockade in EGFR -mutated non–small cell lung cancer. Science Immunology. 5(43). 194 indexed citations
3.
Kamada, Takahiro, Yosuke Togashi, Christopher Tay, et al.. (2019). PD-1 + regulatory T cells amplified by PD-1 blockade promote hyperprogression of cancer. Proceedings of the National Academy of Sciences. 116(20). 9999–10008. 692 indexed citations breakdown →
4.
Tada, Yasuko, Yosuke Togashi, Daisuke Kotani, et al.. (2018). Targeting VEGFR2 with Ramucirumab strongly impacts effector/ activated regulatory T cells and CD8+ T cells in the tumor microenvironment. Journal for ImmunoTherapy of Cancer. 6(1). 106–106. 154 indexed citations
5.
Togashi, Yosuke, Takahiro Kamada, Akinori Sasaki, et al.. (2018). Clinicopathological, genomic and immunological features of hyperprogressive disease during PD-1 blockade in gastric cancer patients.. Journal of Clinical Oncology. 36(15_suppl). 4106–4106. 14 indexed citations
6.
Togashi, Yosuke, Yasuko Tada, Daisuke Kotani, et al.. (2018). Immunological impact of ramucirumab on tumor microenvironment in advanced gastric cancer.. Journal of Clinical Oncology. 36(5_suppl). 98–98. 2 indexed citations
7.
Takeuchi, Yoshiko, Atsushi Tanemura, Yasuko Tada, et al.. (2017). Clinical response to PD-1 blockade correlates with a sub-fraction of peripheral central memory CD4+ T cells in patients with malignant melanoma. International Immunology. 30(1). 13–22. 65 indexed citations
8.
Tada, Yasuko, et al.. (1991). Effect of serum treatment on pertussis antibody determination by ELISA.. PubMed. 73. 175–84. 3 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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