Ryo Yamada

16.4k total citations · 1 hit paper
173 papers, 7.0k citations indexed

About

Ryo Yamada is a scholar working on Rheumatology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Ryo Yamada has authored 173 papers receiving a total of 7.0k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Rheumatology, 41 papers in Molecular Biology and 33 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Ryo Yamada's work include Rheumatoid Arthritis Research and Therapies (31 papers), Systemic Lupus Erythematosus Research (25 papers) and Retinal Diseases and Treatments (21 papers). Ryo Yamada is often cited by papers focused on Rheumatoid Arthritis Research and Therapies (31 papers), Systemic Lupus Erythematosus Research (25 papers) and Retinal Diseases and Treatments (21 papers). Ryo Yamada collaborates with scholars based in Japan, United States and France. Ryo Yamada's co-authors include Kazuhiko Yamamoto, Akari Suzuki, Toshihiro Tanaka, Fumihiko Matsuda, Yuta Kochi, Kouichi Ozaki, Tatsuhiko Tsunoda, Yusuke Nakamura, Tetsuji Sawada and Nagahisa Yoshimura and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Nature Genetics.

In The Last Decade

Ryo Yamada

168 papers receiving 6.9k citations

Hit Papers

Functional SNPs in the lymphotoxin-α gene that are associ... 2002 2026 2010 2018 2002 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
Ryo Yamada Japan 44 1.9k 1.6k 1.5k 1.2k 1.2k 173 7.0k
Roel Goldschmeding Netherlands 65 5.4k 2.8× 1.3k 0.8× 1.5k 1.0× 1.4k 1.1× 555 0.4× 259 12.3k
Amr H. Sawalha United States 52 2.0k 1.1× 2.6k 1.6× 2.9k 2.0× 906 0.7× 338 0.3× 158 6.8k
P. Charles United Kingdom 39 931 0.5× 3.0k 1.9× 1.8k 1.2× 520 0.4× 1.3k 1.0× 94 6.1k
Karel Geboes Belgium 52 1.6k 0.9× 528 0.3× 1.4k 1.0× 3.8k 3.1× 673 0.5× 203 9.2k
Fabrizio Conti Italy 47 1.2k 0.6× 3.6k 2.3× 2.0k 1.4× 643 0.5× 762 0.6× 320 6.6k
Hideki Nomura Japan 33 1.3k 0.7× 591 0.4× 732 0.5× 567 0.5× 508 0.4× 139 4.7k
Mark Haas United States 71 3.8k 2.0× 1.9k 1.2× 3.7k 2.5× 501 0.4× 605 0.5× 238 16.5k
Naoyuki Kamatani Japan 51 2.8k 1.5× 1.1k 0.7× 1.3k 0.9× 1.5k 1.2× 323 0.3× 179 8.9k
Anthony P. Weetman United Kingdom 60 1.6k 0.8× 681 0.4× 3.5k 2.4× 2.5k 2.0× 624 0.5× 218 11.2k
Robert J. Moots United Kingdom 47 1.7k 0.9× 2.7k 1.7× 3.6k 2.5× 428 0.3× 459 0.4× 176 8.2k

Countries citing papers authored by Ryo Yamada

Since Specialization
Citations

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

Fields of papers citing papers by Ryo Yamada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ryo Yamada

This figure shows the co-authorship network connecting the top 25 collaborators of Ryo Yamada. A scholar is included among the top collaborators of Ryo Yamada 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 Ryo Yamada. Ryo Yamada 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.
Higasa, Koichiro, Yoichiro Kamatani, Takahisa Kawaguchi, et al.. (2025). Whole-genome sequencing of 3135 individuals representing the genetic diversity of the Japanese population. Journal of Human Genetics. 71(4). 223–230.
2.
Yamada, Ryo, et al.. (2024). Generation and Application of All Possible Conformations of Cyclic Tryptophan within and beyond Post-translational Modification. The Journal of Organic Chemistry. 90(1). 623–635. 1 indexed citations
3.
Mori, Kentaro, et al.. (2024). Giant Aneurysm in the V1 Segment of Vertebral Artery: A Case Report and Literature Review. NMC Case Report Journal. 11(0). 327–332.
4.
Yamada, Ryo, Masanori Tani, & Minehiro Nishiyama. (2023). EFFECT OF OUT-OF-PLANE LOADING CONDITIONS ON SHEAR BEHAVIOR OF RC SHEAR WALLS. 69B(0). 256–267.
5.
Cui, Guangwei, Akihiro Shimba, Jianshi Jin, et al.. (2023). CD45 alleviates airway inflammation and lung fibrosis by limiting expansion and activation of ILC2s. Proceedings of the National Academy of Sciences. 120(36). e2215941120–e2215941120. 9 indexed citations
6.
Zheng, Cheng, et al.. (2023). Delving into gene-set multiplex networks facilitated by a k-nearest neighbor-based measure of similarity. Computational and Structural Biotechnology Journal. 21. 4988–5002.
7.
Okamoto, Y., et al.. (2022). Comparative Study of Transcriptome in the Hearts Isolated from Mice, Rats, and Humans. Biomolecules. 12(6). 859–859. 3 indexed citations
8.
Uchida, Yutaka, et al.. (2021). Integrated analysis of cell shape and movement in moving frame. Biology Open. 10(3). 3 indexed citations
9.
Cheng, Jian, et al.. (2021). Data-driven comparison of multiple high-dimensional single-cell expression profiles. Journal of Human Genetics. 67(4). 215–221. 5 indexed citations
11.
Yamada, Ryo, et al.. (2020). Interpretation of omics data analyses. Journal of Human Genetics. 66(1). 93–102. 52 indexed citations
12.
Muro, Shigeo, Yasuharu Tabara, Hisako Matsumoto, et al.. (2016). Relationship Among Chlamydia and Mycoplasma Pneumoniae Seropositivity, IKZF1 Genotype and Chronic Obstructive Pulmonary Disease in A General Japanese Population. Medicine. 95(15). e3371–e3371. 14 indexed citations
13.
Setoh, Kazuya, Chikashi Terao, Shigeo Muro, et al.. (2015). Three missense variants of metabolic syndrome-related genes are associated with alpha-1 antitrypsin levels. Nature Communications. 6(1). 7754–7754. 25 indexed citations
14.
Miyake, Masahiro, Kenji Yamashiro, Hideo Nakanishi, et al.. (2013). Heritability Estimation of Axial Length and Refractive Error Explained by Genome-Wide Single Nucleotide Polymorphisms. Investigative Ophthalmology & Visual Science. 54(15). 1734–1734. 2 indexed citations
15.
Yoshimura, Koji, Takeo Nakayama, Akihiro Sekine, et al.. (2012). B‐type natriuretic peptide as an independent correlate of nocturnal voiding in Japanese women. Neurourology and Urodynamics. 31(8). 1266–1271. 17 indexed citations
16.
Yamada, Ryo, et al.. (2011). Population Model–Based Inter-Diplotype Similarity Measure for Accurate Diplotype Clustering. Journal of Computational Biology. 19(1). 55–67. 1 indexed citations
17.
Kochi, Yuta, Keiko Myouzen, Ryo Yamada, et al.. (2009). FCRL3, an Autoimmune Susceptibility Gene, Has Inhibitory Potential on B-Cell Receptor-Mediated Signaling. The Journal of Immunology. 183(9). 5502–5510. 76 indexed citations
18.
Yamada, Ryo & Yukinori Okada. (2008). An optimal dose‐effect mode trend test for SNP genotype tables. Genetic Epidemiology. 33(2). 114–127. 13 indexed citations
19.
Yamamoto, Kazuhiko & Ryo Yamada. (2005). Genome-wide single nucleotide polymorphism analyses of rheumatoid arthritis. Journal of Autoimmunity. 25. 12–15. 13 indexed citations
20.
Yamada, Ryo, Masaki Murakami, & Takahiro Tagami. (2003). Zircon fission track annealing: Short-term heating experiment toward the detection of frictional heat along active faults. GeCAS. 67(18). 548. 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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