Kazuo Ikeda

14.2k total citations
358 papers, 11.5k citations indexed

About

Kazuo Ikeda is a scholar working on Molecular Biology, Surgery and Cellular and Molecular Neuroscience. According to data from OpenAlex, Kazuo Ikeda has authored 358 papers receiving a total of 11.5k indexed citations (citations by other indexed papers that have themselves been cited), including 95 papers in Molecular Biology, 75 papers in Surgery and 52 papers in Cellular and Molecular Neuroscience. Recurrent topics in Kazuo Ikeda's work include Liver physiology and pathology (37 papers), Neurobiology and Insect Physiology Research (34 papers) and Liver Disease Diagnosis and Treatment (23 papers). Kazuo Ikeda is often cited by papers focused on Liver physiology and pathology (37 papers), Neurobiology and Insect Physiology Research (34 papers) and Liver Disease Diagnosis and Treatment (23 papers). Kazuo Ikeda collaborates with scholars based in Japan, United States and Germany. Kazuo Ikeda's co-authors include J. H. Koenig, Toshio Kosaka, Norifumi Kawada, C. A. G. Wiersma, Scott L. Friedman, Shizuya Saika, Katsutoshi Yoshizato, Osamu Yamanaka, Yuji Nakajima and Katsuro Tomita and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Kazuo Ikeda

341 papers receiving 11.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kazuo Ikeda Japan 56 4.4k 2.2k 2.0k 1.9k 1.6k 358 11.5k
Richard A. Lang United States 70 10.7k 2.5× 2.2k 1.0× 1.3k 0.7× 1.5k 0.8× 1.2k 0.7× 181 19.3k
Takashi Nagasawa Japan 67 6.4k 1.5× 1.7k 0.8× 1.0k 0.5× 816 0.4× 269 0.2× 224 22.3k
S M Hsu United States 23 5.1k 1.2× 1.1k 0.5× 2.5k 1.2× 1.3k 0.7× 237 0.2× 36 15.2k
Florent Ginhoux Singapore 82 9.7k 2.2× 1.1k 0.5× 1.5k 0.7× 2.8k 1.5× 906 0.6× 254 35.2k
Sabine Werner Switzerland 90 15.8k 3.6× 4.3k 2.0× 1.1k 0.5× 2.4k 1.3× 1.1k 0.7× 343 35.0k
Leslie A. Leinwand United States 88 13.5k 3.1× 2.0k 0.9× 1.5k 0.7× 1.5k 0.8× 275 0.2× 330 24.9k
Laurence Raine United States 9 5.2k 1.2× 1.2k 0.6× 2.8k 1.4× 1.5k 0.8× 243 0.2× 15 16.5k
Antoon F.M. Moorman Netherlands 74 13.2k 3.0× 947 0.4× 815 0.4× 3.1k 1.6× 442 0.3× 266 18.9k
Masaru Okabe Japan 94 14.3k 3.3× 2.5k 1.2× 2.3k 1.2× 1.9k 1.0× 587 0.4× 404 30.5k
Steffen Jung Israel 95 12.4k 2.8× 964 0.4× 3.1k 1.5× 3.5k 1.9× 462 0.3× 230 49.4k

Countries citing papers authored by Kazuo Ikeda

Since Specialization
Citations

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

Fields of papers citing papers by Kazuo Ikeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kazuo Ikeda

This figure shows the co-authorship network connecting the top 25 collaborators of Kazuo Ikeda. A scholar is included among the top collaborators of Kazuo Ikeda 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 Kazuo Ikeda. Kazuo Ikeda 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.
Matsubara, Tsutomu, Hayato Urushima, Masahiko Kinoshita, et al.. (2025). Cdc42 is crucial for the early regulation of hepatic stellate cell activation. American Journal of Physiology-Cell Physiology. 328(3). C757–C775.
2.
Matsubara, Tsutomu, Misako Sato, Hayato Urushima, et al.. (2025). Lawsone can suppress liver fibrosis by inhibition of YAP signaling and induction of CYGB expression in hepatic stellate cells. Biomedicine & Pharmacotherapy. 191. 118520–118520.
3.
Nakamura, Yuta, et al.. (2023). Medium-term Outcomes of Excision Using Surgical Microscope of Tenosynovial Giant Cell Tumors of the Hand. Anticancer Research. 44(1). 375–378. 1 indexed citations
4.
Urushima, Hayato, Tsutomu Matsubara, Masaaki Miyakoshi, et al.. (2023). Hypo-osmolarity induces apoptosis resistance via TRPV2-mediated AKT-Bcl-2 pathway. American Journal of Physiology-Gastrointestinal and Liver Physiology. 324(3). G219–G230. 5 indexed citations
5.
Sato, Misako, Yasutoshi Kido, Hayato Urushima, et al.. (2022). Nitric Oxide Derived from Cytoglobin-Deficient Hepatic Stellate Cells Causes Suppression of Cytochrome c Oxidase Activity in Hepatocytes. Antioxidants and Redox Signaling. 38(7-9). 463–479. 9 indexed citations
6.
Sato, Misako, Tsutomu Matsubara, Lisa Longato, et al.. (2020). TGF-β1-driven reduction of cytoglobin leads to oxidative DNA damage in stellate cells during non-alcoholic steatohepatitis. Journal of Hepatology. 73(4). 882–895. 31 indexed citations
7.
Bito, Seiji, Shigeki Miyata, Kiyoshi Migita, et al.. (2015). Mechanical prophylaxis is a heparin-independent risk for anti–platelet factor 4/heparin antibody formation after orthopedic surgery. Blood. 127(8). 1036–1043. 25 indexed citations
8.
Enomoto, Masaru, Hideki Fujii, Yumiko Sekiya, et al.. (2012). MicroRNA-221/222 upregulation indicates the activation of stellate cells and the progression of liver fibrosis. Gut. 61(11). 1600–1609. 209 indexed citations
9.
Ikeda, Kazuo. (2009). [Bone fracture and the healing mechanisms. Application of the extracorporeal shock wave on treatment of fracture].. PubMed. 19(5). 718–25. 4 indexed citations
10.
Inagaki, Yutaka, Tomoyuki Nemoto, Miwa Kushida, et al.. (2003). Interferon Alfa Down–Regulates Collagen Gene Transcription and Suppresses Experimental Hepatic Fibrosis in Mice. Hepatology. 38(4). 890–899. 104 indexed citations
11.
Ikeda, Kazuo, et al.. (2003). Liver Fibrosis and DDR2 Signaling. 35(3). 165–168. 1 indexed citations
12.
Sudo, Kayoko, Masato Maekawa, Makoto Shioya, et al.. (1992). Molecular analysis of genetic mutation in electrophoretic variant of human lactate dehydrogenase-A(M) subunit.. PubMed. 27(6). 1051–7. 4 indexed citations
13.
Ikeda, Kazuo & Susumu Nomura. (1990). Plexiform neurogenic tumors.. 41(10). 1503–1509. 1 indexed citations
14.
Ikeda, Kazuo, et al.. (1986). Plasma constituents of rainbow trout yearlings with reference to the influence of n-butyl alcohol added to commercial feeds.. NIPPON SUISAN GAKKAISHI. 52(12). 2149–2154. 1 indexed citations
15.
Ikeda, Kazuo, et al.. (1981). . NIPPON SUISAN GAKKAISHI. 47(3). 371–376. 2 indexed citations
16.
Ikeda, Kazuo, et al.. (1977). . JOURNAL OF THE JAPAN WELDING SOCIETY. 46(11). 825–831. 1 indexed citations
17.
Ueda, Yukio, et al.. (1976). Characteristics of Brittle Fracture Under Bi-axial Tensile Load. OUKA (Osaka University Knowledge Archive) (Osaka University). 5(2). 169–177. 3 indexed citations
18.
Kihara, Hiroshi, Michio Inagaki, & Kazuo Ikeda. (1969). Welding Cracks and Notch-Toughness of Heat-Affected Zone in High-Strength Steels. JOURNAL OF THE JAPAN WELDING SOCIETY. 38(1). 33–54.
19.
Ikeda, Kazuo, et al.. (1968). 6. On Brittle Fracture Initiation (First Report-Deep Notch Test). 1. 49–61. 1 indexed citations
20.
Ikeda, Kazuo, et al.. (1960). Dispersibility of Several Fine Powders in Solid Paraffin on the Mechanism of its Hydrophobilization. The Journal of the Society of Chemical Industry Japan. 63(1). 99–104.

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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