Eisuke Mekada

10.4k total citations · 2 hit papers
130 papers, 8.4k citations indexed

About

Eisuke Mekada is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Eisuke Mekada has authored 130 papers receiving a total of 8.4k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Molecular Biology, 51 papers in Immunology and 38 papers in Oncology. Recurrent topics in Eisuke Mekada's work include Toxin Mechanisms and Immunotoxins (42 papers), Transgenic Plants and Applications (31 papers) and Monoclonal and Polyclonal Antibodies Research (31 papers). Eisuke Mekada is often cited by papers focused on Toxin Mechanisms and Immunotoxins (42 papers), Transgenic Plants and Applications (31 papers) and Monoclonal and Polyclonal Antibodies Research (31 papers). Eisuke Mekada collaborates with scholars based in Japan, United States and Thailand. Eisuke Mekada's co-authors include Ryo Iwamoto, Shigeki Higashiyama, Michael Klagsbrun, Tsuyoshi Uchida, Yoshio Okada, Masaru Yamaizumi, Naoyuki Taniguchi, Shingo Miyamoto, Toshiyuki Umata and T. Mitamura and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Eisuke Mekada

129 papers receiving 8.2k citations

Hit Papers

One molecule of diphtheria toxin fragment a introduced in... 1978 2026 1994 2010 1978 2000 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
Eisuke Mekada Japan 48 4.2k 2.4k 2.0k 1.4k 1.1k 130 8.4k
Gregory D. Plowman United States 59 8.6k 2.0× 1.6k 0.7× 5.0k 2.6× 1.5k 1.0× 2.2k 1.9× 98 13.8k
C Gorman United States 20 6.8k 1.6× 2.1k 0.9× 2.2k 1.1× 647 0.5× 561 0.5× 23 11.5k
Joel S. Hayflick United States 30 4.3k 1.0× 1.9k 0.8× 1.9k 0.9× 479 0.3× 411 0.4× 42 8.0k
Diane Pennica United States 46 6.1k 1.4× 3.7k 1.5× 3.1k 1.6× 500 0.4× 469 0.4× 89 12.4k
Takahiro Kunisada Japan 49 7.1k 1.7× 2.4k 1.0× 2.5k 1.3× 510 0.4× 2.1k 1.9× 209 12.6k
Martin L. Breitman Canada 44 11.0k 2.6× 1.4k 0.6× 3.0k 1.5× 792 0.6× 2.1k 1.9× 95 13.8k
Keith C. Robbins United States 48 5.1k 1.2× 1.6k 0.7× 1.8k 0.9× 818 0.6× 896 0.8× 94 8.1k
Ashley R. Dunn Australia 50 3.6k 0.9× 4.9k 2.0× 2.0k 1.0× 618 0.4× 492 0.4× 101 10.0k
Peter Besmer United States 65 6.5k 1.5× 4.8k 2.0× 2.4k 1.2× 1.4k 1.0× 1.2k 1.1× 119 16.6k
S A Aaronson United States 46 5.8k 1.4× 1.1k 0.5× 3.1k 1.6× 811 0.6× 1.1k 1.0× 98 9.6k

Countries citing papers authored by Eisuke Mekada

Since Specialization
Citations

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

Fields of papers citing papers by Eisuke Mekada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eisuke Mekada

This figure shows the co-authorship network connecting the top 25 collaborators of Eisuke Mekada. A scholar is included among the top collaborators of Eisuke Mekada 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 Eisuke Mekada. Eisuke Mekada 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.
Nonthabenjawan, Nutthawan, Ratana Tacharoenmuang, Kriangsak Ruchusatsawat, et al.. (2021). Spread of genetically similar noroviruses in Bangkok, Thailand, through symptomatic and asymptomatic individuals. Heliyon. 7(10). e08250–e08250. 3 indexed citations
2.
Yoshida, Yuichi, Shinichi Kiso, Takashi Kizu, et al.. (2013). Conditional loss of heparin-binding EGF-like growth factor results in enhanced liver fibrosis after bile duct ligation in mice. Biochemical and Biophysical Research Communications. 437(2). 185–191. 34 indexed citations
3.
Murata, Takuya, Hiroto Mizushima, Ichino Chinen, et al.. (2011). HB-EGF and PDGF Mediate Reciprocal Interactions of Carcinoma Cells with Cancer-Associated Fibroblasts to Support Progression of Uterine Cervical Cancers. Cancer Research. 71(21). 6633–6642. 78 indexed citations
4.
Miyamoto, Shingo, Ryo Iwamoto, Akiko Furuya, et al.. (2011). A Novel Anti-Human HB-EGF Monoclonal Antibody with Multiple Antitumor Mechanisms against Ovarian Cancer Cells. Clinical Cancer Research. 17(21). 6733–6741. 25 indexed citations
6.
Miyado, Kenji, Keiichi Yoshida, Kazuo Yamagata, et al.. (2008). The fusing ability of sperm is bestowed by CD9-containing vesicles released from eggs in mice. Proceedings of the National Academy of Sciences. 105(35). 12921–12926. 154 indexed citations
7.
Yotsumoto, Fusanori, Hiroshi Yagi, Satoshi O. Suzuki, et al.. (2007). Validation of HB-EGF and amphiregulin as targets for human cancer therapy. Biochemical and Biophysical Research Communications. 365(3). 555–561. 119 indexed citations
8.
Wang, Xiaobiao, Hiroto Mizushima, Satoshi Adachi, et al.. (2006). Cytoplasmic Domain Phosphorylation of Heparin-Binding EGF-like Growth Factor. Cell Structure and Function. 31(1). 15–27. 25 indexed citations
9.
Miyamoto, Shingo, Michinari Hirata, Ayano Yamazaki, et al.. (2004). Heparin-Binding EGF-Like Growth Factor Is a Promising Target for Ovarian Cancer Therapy. Cancer Research. 64(16). 5720–5727. 155 indexed citations
10.
Miyamoto, Shingo & Eisuke Mekada. (2004). [Biological behavior of ovarian cancer].. PubMed. 62 Suppl 10. 458–62. 1 indexed citations
11.
Iwamoto, Ryo, Satoru Yamazaki, Masanori Asakura, et al.. (2003). Heparin-binding EGF-like growth factor and ErbB signaling is essential for heart function. Proceedings of the National Academy of Sciences. 100(6). 3221–3226. 281 indexed citations
12.
Yu, Xiaochun, et al.. (2002). Ligand-independent Dimer Formation of Epidermal Growth Factor Receptor (EGFR) Is a Step Separable from Ligand-induced EGFR Signaling. Molecular Biology of the Cell. 13(7). 2547–2557. 170 indexed citations
13.
Miyado, Kenji, Gen Yamada, Shuichi Yamada, et al.. (2000). Requirement of CD9 on the Egg Plasma Membrane for Fertilization. Science. 287(5451). 321–324. 547 indexed citations breakdown →
14.
Doh‐ura, Katsumi, Eisuke Mekada, Koji Ogomori, & Toru Iwaki. (2000). Enhanced CD9 Expression in the Mouse and Human Brains Infected with Transmissible Spongiform Encephalopathies. Journal of Neuropathology & Experimental Neurology. 59(9). 774–785. 21 indexed citations
16.
Nakagawa, Takatoshi, Shigeki Higashiyama, T. Mitamura, Eisuke Mekada, & Naoyuki Taniguchi. (1996). Amino-terminal Processing of Cell Surface Heparin-binding Epidermal Growth Factor-like Growth Factor Up-regulates Its Juxtacrine but Not Its Paracrine Growth Factor Activity. Journal of Biological Chemistry. 271(48). 30858–30863. 31 indexed citations
18.
Mekada, Eisuke. (1993). Diphtheria toxin receptor.. Nippon Saikingaku Zasshi. 48(5). 685–692. 4 indexed citations
19.
Mekada, Eisuke, Hideki Senoh, Ryo Iwamoto, Yasunori Okada, & Takafumi Uchida. (1991). Purification of diphtheria toxin receptor from Vero cells.. Journal of Biological Chemistry. 266(30). 20457–20462. 28 indexed citations
20.
Hayakawa, Satoshi, Takahiro Uchida, Eisuke Mekada, Kiyoharu Takamatsu, & Yoshiaki Okada. (1981). Mono clonal antibodies against diphtheria toxin and analysis of diphtheria toxin using them. Cell Structure and Function. 6(4). 434.

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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