Kai Shibata

466 total citations
13 papers, 371 citations indexed

About

Kai Shibata is a scholar working on Pulmonary and Respiratory Medicine, Immunology and Rheumatology. According to data from OpenAlex, Kai Shibata has authored 13 papers receiving a total of 371 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Pulmonary and Respiratory Medicine, 4 papers in Immunology and 3 papers in Rheumatology. Recurrent topics in Kai Shibata's work include Pediatric health and respiratory diseases (3 papers), T-cell and B-cell Immunology (3 papers) and Rheumatoid Arthritis Research and Therapies (3 papers). Kai Shibata is often cited by papers focused on Pediatric health and respiratory diseases (3 papers), T-cell and B-cell Immunology (3 papers) and Rheumatoid Arthritis Research and Therapies (3 papers). Kai Shibata collaborates with scholars based in Japan. Kai Shibata's co-authors include Hirayasu Kai, Satoko Tahara‐Hanaoka, Akira Shibuya, Kazuko Shibuya, Shin‐ichiro Honda, Yumi Yamashita, Teruhito Yasui, Akiko Iguchi‐Manaka, Hitoshi Kikutani and Tsukasa Nabekura and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine and PLoS ONE.

In The Last Decade

Kai Shibata

10 papers receiving 367 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kai Shibata Japan 7 309 102 35 31 27 13 371
Saumya Maru United States 8 203 0.7× 69 0.7× 84 2.4× 13 0.4× 24 0.9× 12 328
Valérie Pasqualetto France 7 461 1.5× 63 0.6× 69 2.0× 31 1.0× 10 0.4× 14 508
Lise Kveberg Norway 16 475 1.5× 92 0.9× 104 3.0× 49 1.6× 13 0.5× 23 562
Asami Hanazawa Japan 9 246 0.8× 70 0.7× 54 1.5× 22 0.7× 21 0.8× 12 331
Cyrille Mionnet France 10 273 0.9× 102 1.0× 78 2.2× 8 0.3× 47 1.7× 10 382
Loreto Parga‐Vidal Netherlands 7 355 1.1× 115 1.1× 50 1.4× 18 0.6× 10 0.4× 9 432
Hristo Georgiev Germany 10 299 1.0× 112 1.1× 52 1.5× 8 0.3× 6 0.2× 18 357
Thordis Hohnstein Germany 4 173 0.6× 63 0.6× 54 1.5× 7 0.2× 18 0.7× 5 252
Emma Gomez-Rivas United States 4 116 0.4× 42 0.4× 54 1.5× 21 0.7× 8 0.3× 6 207
Nurhidaya Binte Shadan Singapore 5 217 0.7× 47 0.5× 55 1.6× 9 0.3× 8 0.3× 5 267

Countries citing papers authored by Kai Shibata

Since Specialization
Citations

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

Fields of papers citing papers by Kai Shibata

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kai Shibata

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

All Works

13 of 13 papers shown
1.
Imanishi, Aya, et al.. (2022). Prevalence, incidence, and medications of narcolepsy in Japan: a descriptive observational study using a health insurance claims database. Sleep and Biological Rhythms. 20(4). 585–594. 8 indexed citations
5.
Ishiguro, Naoki, et al.. (2019). Investigation of the predictors of the response to Iguratimod therapy: A post-hoc analysis of post-marketing surveillance study. Modern Rheumatology. 30(4). 626–632. 3 indexed citations
7.
Setoguchi, Yasuhiro, et al.. (2016). Pharmacological effects of lysozyme on COPD and bronchial asthma with sputum: A randomized, placebo-controlled, small cohort, cross-over study. Pulmonary Pharmacology & Therapeutics. 37. 73–80. 16 indexed citations
8.
Fukuchi, Yoshinosuke, et al.. (2016). Prevention of COPD exacerbation by lysozyme: a double-blind, randomized, placebo-controlled study. International Journal of COPD. 11. 831–831. 9 indexed citations
9.
Ohbayashi, Hiroyuki, et al.. (2014). Pharmacological effect of lysozyme for COPD and bronchial asthma with sputum: A randomized, placebo-controlled, cross-over study. European Respiratory Journal. 44(Suppl 58). P1502–P1502. 1 indexed citations
10.
Nabekura, Tsukasa, Kazuko Shibuya, Hirayasu Kai, et al.. (2010). Critical role of DNAX accessory molecule-1 (DNAM-1) in the development of acute graft-versus-host disease in mice. Proceedings of the National Academy of Sciences. 107(43). 18593–18598. 52 indexed citations
11.
Iguchi‐Manaka, Akiko, Hirayasu Kai, Yumi Yamashita, et al.. (2008). Accelerated tumor growth in mice deficient in DNAM-1 receptor. The Journal of Experimental Medicine. 205(13). 2959–2964. 221 indexed citations
12.
Wang, Yinan, Kazuko Shibuya, Yumi Yamashita, et al.. (2008). LFA-1 decreases the antigen dose for T cell activation in vivo. International Immunology. 20(9). 1119–1127. 25 indexed citations
13.
Wang, Yinan, Hirayasu Kai, Fei Chang, et al.. (2006). A critical role of LFA-1 in the development of Th17 cells and induction of experimental autoimmune encephalomyelytis. Biochemical and Biophysical Research Communications. 353(4). 857–862. 35 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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