Yusuke Yanagi

12.2k total citations · 2 hit papers
137 papers, 10.0k citations indexed

About

Yusuke Yanagi is a scholar working on Epidemiology, Immunology and Infectious Diseases. According to data from OpenAlex, Yusuke Yanagi has authored 137 papers receiving a total of 10.0k indexed citations (citations by other indexed papers that have themselves been cited), including 97 papers in Epidemiology, 48 papers in Immunology and 43 papers in Infectious Diseases. Recurrent topics in Yusuke Yanagi's work include Virology and Viral Diseases (89 papers), Respiratory viral infections research (52 papers) and Parvovirus B19 Infection Studies (20 papers). Yusuke Yanagi is often cited by papers focused on Virology and Viral Diseases (89 papers), Respiratory viral infections research (52 papers) and Parvovirus B19 Infection Studies (20 papers). Yusuke Yanagi collaborates with scholars based in Japan, United States and Canada. Yusuke Yanagi's co-authors include Nobuyuki Ono, Hironobu Tatsuo, Makoto Takeda, Tak W. Mak, Yasunobu Yoshikai, Shinji Ohno, Kotaro Tanaka, Stephen P. Clark, Takao Hashiguchi and Hiroko Minagawa and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Yusuke Yanagi

136 papers receiving 9.7k citations

Hit Papers

A human T cell-specific cDNA clone encodes a protein havi... 1984 2026 1998 2012 1984 2000 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yusuke Yanagi Japan 53 5.2k 4.3k 2.5k 1.9k 1.6k 137 10.0k
Robert E. Lanford United States 56 5.3k 1.0× 1.6k 0.4× 1.6k 0.6× 4.1k 2.2× 1.1k 0.7× 170 11.8k
Roberto Cattaneo United States 76 9.7k 1.9× 3.2k 0.7× 4.2k 1.7× 3.4k 1.8× 5.6k 3.5× 286 16.2k
William W. Hall Ireland 48 2.0k 0.4× 3.3k 0.8× 1.7k 0.7× 1.2k 0.6× 642 0.4× 252 7.8k
Gerd Sutter Germany 54 3.9k 0.8× 4.4k 1.0× 2.4k 1.0× 2.4k 1.3× 2.1k 1.3× 211 10.0k
Jeffrey A. Frelinger United States 49 1.2k 0.2× 4.6k 1.1× 1.3k 0.5× 2.1k 1.1× 1.0k 0.6× 214 8.0k
Stephen Goodbourn United Kingdom 47 3.5k 0.7× 5.2k 1.2× 2.8k 1.1× 3.5k 1.8× 1.5k 1.0× 93 10.7k
Gabriella Campadelli‐Fiume Italy 50 5.5k 1.1× 2.1k 0.5× 589 0.2× 1.5k 0.8× 2.2k 1.4× 205 7.4k
Jovan Pavlovic Switzerland 40 2.5k 0.5× 4.7k 1.1× 1.8k 0.7× 2.3k 1.2× 967 0.6× 84 8.2k
Hartmut Hengel Germany 55 6.1k 1.2× 5.4k 1.2× 1.1k 0.4× 1.6k 0.9× 554 0.3× 180 10.0k
Ulrich H. Koszinowski Germany 78 11.5k 2.2× 8.5k 2.0× 1.5k 0.6× 3.7k 1.9× 1.6k 1.0× 221 17.5k

Countries citing papers authored by Yusuke Yanagi

Since Specialization
Citations

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

Fields of papers citing papers by Yusuke Yanagi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yusuke Yanagi

This figure shows the co-authorship network connecting the top 25 collaborators of Yusuke Yanagi. A scholar is included among the top collaborators of Yusuke Yanagi 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 Yusuke Yanagi. Yusuke Yanagi 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.
Zamora‐Valdés, Daniel, et al.. (2025). Pediatric living donor liver transplantation for small infants with biliary atresia using interposition portal vein grafts: A multicenter cohort study. Liver Transplantation. 31(7). 890–896. 1 indexed citations
2.
Uchida, Hajime, Seisuke Sakamoto, Toshimasa Nakao, et al.. (2022). Preemptive liver transplant in two patients with primary hyperoxaluria type 1: Clinical significance of nephrolithiasis and nephrocalcinosis. Pediatric Transplantation. 26(8). e14380–e14380.
3.
Kubota, Marie, et al.. (2020). Lysosome-Associated Membrane Proteins Support the Furin-Mediated Processing of the Mumps Virus Fusion Protein. Journal of Virology. 94(12). 12 indexed citations
4.
Hashiguchi, Takao, Marnie L. Fusco, Zachary A. Bornholdt, et al.. (2015). Structural Basis for Marburg Virus Neutralization by a Cross-Reactive Human Antibody. Cell. 160(5). 904–912. 103 indexed citations
5.
Shirogane, Yuta, Shumpei Watanabe, & Yusuke Yanagi. (2015). Cooperative Interaction Within RNA Virus Mutant Spectra. Current topics in microbiology and immunology. 392. 219–229. 12 indexed citations
6.
Ichinohe, Takeshi, Tatsuya Yamazaki, Takumi Koshiba, & Yusuke Yanagi. (2013). Mitochondrial protein mitofusin 2 is required for NLRP3 inflammasome activation after RNA virus infection. Proceedings of the National Academy of Sciences. 110(44). 17963–17968. 227 indexed citations
7.
Hashiguchi, Takao, Toyoyuki Ose, Marie Kubota, et al.. (2011). Structure of the measles virus hemagglutinin bound to its cellular receptor SLAM. Nature Structural & Molecular Biology. 18(2). 135–141. 181 indexed citations
8.
Navaratnarajah, Chanakha K., Sompong Vongpunsawad, Numan Oezguen, et al.. (2008). Dynamic Interaction of the Measles Virus Hemagglutinin with Its Receptor Signaling Lymphocytic Activation Molecule (SLAM, CD150). Journal of Biological Chemistry. 283(17). 11763–11771. 60 indexed citations
9.
McCausland, Megan, et al.. (2007). SAP Regulation of Follicular Helper CD4 T Cell Development and Humoral Immunity Is Independent of SLAM and Fyn Kinase. The Journal of Immunology. 178(2). 817–828. 80 indexed citations
10.
Bouche, Fabienne B., André Steinmetz, Yusuke Yanagi, & Claude P. Muller. (2005). Induction of broadly neutralizing antibodies against measles virus mutants using a polyepitope vaccine strategy. Vaccine. 23(17-18). 2074–2077. 15 indexed citations
11.
Davidson, Dominique, Shaohua Zhang, Hao Wang, et al.. (2004). Genetic Evidence Linking SAP, the X-Linked Lymphoproliferative Gene Product, to Src-Related Kinase FynT in TH2 Cytokine Regulation. Immunity. 21(5). 707–717. 120 indexed citations
12.
Yanagi, Yusuke, Nobuyuki Ono, Hironobu Tatsuo, Koji Hashimoto, & Hiroko Minagawa. (2002). Measles Virus Receptor SLAM (CD150). Virology. 299(2). 155–161. 66 indexed citations
13.
Yanagi, Yusuke. (2001). . Uirusu. 51(2). 201–208. 9 indexed citations
14.
Tatsuo, Hironobu, Nobuyuki Ono, Kotaro Tanaka, & Yusuke Yanagi. (2000). . Uirusu. 50(2). 289–296. 8 indexed citations
15.
16.
Minagawa, Hiroko, et al.. (1999). Enhanced IFN-γ Production in Vitro by CD8+ T Cells in Hemophiliacs with AIDS as Demonstrated on the Single-Cell Level. Clinical Immunology. 92(1). 111–117. 6 indexed citations
18.
Iwata, Kazunori, Tsukasa Seya, Yusuke Yanagi, et al.. (1995). Diversity of Sites for Measles Virus Binding and for Inactivation of Complement C3b and C4b on Membrane Cofactor Protein CD46. Journal of Biological Chemistry. 270(25). 15148–15152. 118 indexed citations
19.
Yoshikura, Hiroshi, et al.. (1994). L cell clone developing plaques upon infection with measles virus (Edmonston strain). Archives of Virology. 139(3-4). 427–430. 1 indexed citations
20.
Yanagi, Yusuke, et al.. (1989). Post-transcriptional allelic exclusion of two functionally rearranged T cell receptor α genes. International Immunology. 1(3). 281–288. 27 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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