Ryusuke Nabeshima

632 total citations
9 papers, 491 citations indexed

About

Ryusuke Nabeshima is a scholar working on Immunology, Oncology and Genetics. According to data from OpenAlex, Ryusuke Nabeshima has authored 9 papers receiving a total of 491 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Immunology, 4 papers in Oncology and 4 papers in Genetics. Recurrent topics in Ryusuke Nabeshima's work include Immune Response and Inflammation (3 papers), Blood disorders and treatments (3 papers) and Immune Cell Function and Interaction (3 papers). Ryusuke Nabeshima is often cited by papers focused on Immune Response and Inflammation (3 papers), Blood disorders and treatments (3 papers) and Immune Cell Function and Interaction (3 papers). Ryusuke Nabeshima collaborates with scholars based in Japan and Czechia. Ryusuke Nabeshima's co-authors include Shiro Shibayama, Tamon Hayashi, Taku Okazaki, Shunsuke Chikuma, Takao Yoshida, Seigo Terawaki, Tasuku Honjo, Hiroshi Handa, Osamu Iwase and Makoto Yaguchi and has published in prestigious journals such as Nature, The Journal of Immunology and International Journal of Molecular Medicine.

In The Last Decade

Ryusuke Nabeshima

7 papers receiving 484 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ryusuke Nabeshima Japan	7	200	176	133	108	51	9	491
Mary Riwes United States	12	173 0.9×	197 1.1×	132 1.0×	262 2.4×	73 1.4×	33	516
Najla Arshad India	9	193 1.0×	148 0.8×	80 0.6×	42 0.4×	79 1.5×	12	529
Daniel Peltier United States	14	232 1.2×	252 1.4×	88 0.7×	116 1.1×	103 2.0×	32	590
Diana Hanekamp Netherlands	11	98 0.5×	283 1.6×	76 0.6×	267 2.5×	27 0.5×	16	559
Tai‐Ju Hwang South Korea	11	128 0.6×	179 1.0×	70 0.5×	110 1.0×	56 1.1×	25	489
Sophia Siu United States	11	213 1.1×	251 1.4×	170 1.3×	16 0.1×	72 1.4×	12	645
Monika Jurkowska Poland	15	208 1.0×	155 0.9×	123 0.9×	35 0.3×	19 0.4×	27	569
Yuhao Jiao China	9	216 1.1×	216 1.2×	54 0.4×	28 0.3×	54 1.1×	14	509
Fréderic Emschermann Germany	10	174 0.9×	225 1.3×	61 0.5×	71 0.7×	22 0.4×	14	522
T J Lawley United States	7	197 1.0×	154 0.9×	79 0.6×	45 0.4×	89 1.7×	11	490

Countries citing papers authored by Ryusuke Nabeshima

Since Specialization

Citations

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

Fields of papers citing papers by Ryusuke Nabeshima

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ryusuke Nabeshima

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

All Works

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9 of 9 papers shown

Yoshimori, Mayumi, Miwako Nishio, Yoichi Maekawa, et al.. (2025). Expression profiling of Epstein–Barr virus-derived microRNA in systemic chronic active EBV disease. International Journal of Hematology. 122(6). 864–876.

Morita, Naoki, Eiji Umemoto, Akio Hayashi, et al.. (2019). GPR31-dependent dendrite protrusion of intestinal CX3CR1+ cells by bacterial metabolites. Nature. 566(7742). 110–114. 163 indexed citations

Chikuma, Shunsuke, Seigo Terawaki, Tamon Hayashi, et al.. (2009). PD-1-Mediated Suppression of IL-2 Production Induces CD8+ T Cell Anergy In Vivo. The Journal of Immunology. 182(11). 6682–6689. 167 indexed citations

Hiramoto, Masaki, Yutaka Kawakami, Ryusuke Nabeshima, et al.. (2004). Identification of differentiation-inducing activity produced by human bone marrow stromal cell line LP101. International Journal of Molecular Medicine. 14(5). 867–72.

Aizawa, Shin, Masaru Nakano, Osamu Iwase, et al.. (1999). Bone marrow stroma from refractory anemia of myelodysplastic syndrome is defective in its ability to support normal CD34-positive cell proliferation and differentiation in vitro. Leukemia Research. 23(3). 239–246. 81 indexed citations

Hiramoto, Masaki, Shin Aizawa, Osamu Iwase, et al.. (1998). Stimulatory effects of substance P on CD34 positive cell proliferation and differentiation in vitro are mediated by the modulation of stromal cell function.. International Journal of Molecular Medicine. 1(2). 347–54. 29 indexed citations

Yaguchi, Makoto, Osamu Iwase, Keisuke Toyama, et al.. (1997). Possible Involvement of Bone Marrow Stromal Cells in Agranulocytosis Caused by Vesnarinone Treatment. Acta Haematologica. 98(3). 140–146. 10 indexed citations

Nabeshima, Ryusuke, et al.. (1997). Effects of vesnarinone on the bone marrow stromal cell-dependent proliferation and differentiation of HL60 cells in vitro.. PubMed. 25(6). 509–15. 13 indexed citations

Aizawa, Sen‐ichi, Makoto Yaguchi, Michel Y. Nakano, et al.. (1994). Hematopoietic supportive function of human bone marrow stromal cell lines established by a recombinant SV40-adenovirus vector.. PubMed. 22(6). 482–7. 28 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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