Masatoshi Tagawa

5.5k total citations
210 papers, 4.6k citations indexed

About

Masatoshi Tagawa is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Masatoshi Tagawa has authored 210 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Molecular Biology, 77 papers in Oncology and 75 papers in Immunology. Recurrent topics in Masatoshi Tagawa's work include Virus-based gene therapy research (69 papers), Immunotherapy and Immune Responses (44 papers) and Cancer Research and Treatments (43 papers). Masatoshi Tagawa is often cited by papers focused on Virus-based gene therapy research (69 papers), Immunotherapy and Immune Responses (44 papers) and Cancer Research and Treatments (43 papers). Masatoshi Tagawa collaborates with scholars based in Japan, United States and China. Masatoshi Tagawa's co-authors include Kiyoko Kawamura, Shigeru Sakiyama, Hideaki Shimada, Jiyang O‐Wang, Hiromitsu Saisho, Osamu Shimozato, Yuji Tada, Ling Yu, Kenzo Hiroshima and Masako Chiyo and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Masatoshi Tagawa

209 papers receiving 4.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Masatoshi Tagawa Japan 35 2.3k 1.7k 1.5k 1.0k 564 210 4.6k
Lorena Landuzzi Italy 37 2.0k 0.9× 1.6k 0.9× 1.5k 1.0× 535 0.5× 545 1.0× 131 4.2k
Claudine Rancourt Canada 33 2.2k 1.0× 1.0k 0.6× 964 0.6× 681 0.7× 472 0.8× 59 3.6k
Shigeo Takaishi Japan 28 1.6k 0.7× 1.5k 0.9× 1.1k 0.7× 380 0.4× 582 1.0× 63 3.8k
Guillermo Mazzolini Argentina 35 1.5k 0.7× 1.5k 0.9× 1.5k 1.0× 918 0.9× 389 0.7× 115 4.0k
Claudia Chiodoni Italy 35 1.7k 0.8× 1.6k 1.0× 2.5k 1.7× 449 0.4× 526 0.9× 83 4.6k
Yasuharu Nishimura Japan 44 2.6k 1.2× 1.8k 1.1× 3.0k 2.0× 436 0.4× 386 0.7× 171 6.0k
Neil I. Goldstein United States 27 2.2k 1.0× 2.1k 1.3× 752 0.5× 718 0.7× 499 0.9× 64 4.3k
Monica Rodolfo Italy 33 2.1k 0.9× 1.4k 0.8× 1.8k 1.2× 392 0.4× 852 1.5× 89 4.0k
Angelica Loskog Sweden 37 1.3k 0.6× 2.8k 1.7× 2.2k 1.5× 1.2k 1.2× 235 0.4× 103 4.6k
Lea Eisenbach Israel 33 2.1k 0.9× 1.5k 0.9× 2.5k 1.6× 570 0.6× 347 0.6× 123 4.4k

Countries citing papers authored by Masatoshi Tagawa

Since Specialization
Citations

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

Fields of papers citing papers by Masatoshi Tagawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masatoshi Tagawa

This figure shows the co-authorship network connecting the top 25 collaborators of Masatoshi Tagawa. A scholar is included among the top collaborators of Masatoshi Tagawa 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 Masatoshi Tagawa. Masatoshi Tagawa 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.
Matsunaga, Wataru, Katsuyuki Hamada, Masatoshi Tagawa, Takao Morinaga, & Akinobu Gotoh. (2021). Cancer Cell-specific Transfection of hCas9 Gene Using Ad5F35 Vector. Anticancer Research. 41(8). 3731–3740. 2 indexed citations
2.
Kubo, Shuji, et al.. (2018). Dual-vector prodrug activator gene therapy using retroviral replicating vectors. Cancer Gene Therapy. 26(5-6). 128–135. 17 indexed citations
3.
Ushigome, Mitsunori, Yoshihiro Nabeya, Hiroaki Soda, et al.. (2018). Multi-panel assay of serum autoantibodies in colorectal cancer. International Journal of Clinical Oncology. 23(5). 917–923. 26 indexed citations
6.
Ma, Guangyu, K Kawamura, Shinya Okamoto, et al.. (2014). Combination of adenoviruses expressing melanoma differentiation-associated gene-7 and chemotherapeutic agents produces enhanced cytotoxicity on esophageal carcinoma. Cancer Gene Therapy. 21(1). 31–37. 9 indexed citations
7.
Kanno, Takeshi, Akinobu Gotoh, Takashi Nakano, Masatoshi Tagawa, & Tomoyuki Nishizaki. (2012). Beneficial oncolytic effect of fiber-substituted conditionally replicating adenovirus on human lung cancer.. PubMed. 32(11). 4891–5. 4 indexed citations
8.
Kawamura, K, Shinya Okamoto, M. Numasaki, et al.. (2011). Adenoviruses-mediated transduction of human oesophageal carcinoma cells with the interferon-λ genes produced anti-tumour effects. British Journal of Cancer. 105(9). 1302–1312. 14 indexed citations
9.
10.
Tagawa, Masatoshi. (2007). Cancer therapy with local oncolysis and topical cytokine secretion. Frontiers in bioscience. 13(13). 2578–2578. 6 indexed citations
11.
Masuda, Keiji, Rika Ouchida, Arata Takeuchi, et al.. (2005). DNA polymerase θ contributes to the generation of C/G mutations during somatic hypermutation of Ig genes. Proceedings of the National Academy of Sciences. 102(39). 13986–13991. 94 indexed citations
12.
Leopoldino, Andréia Machado, Valérie Bergoglio, Jiyang O‐Wang, et al.. (2005). Up-regulation of the error-prone DNA polymerase {kappa} promotes pleiotropic genetic alterations and tumorigenesis.. PubMed. 65(1). 325–30. 81 indexed citations
13.
Wada, Akihiko, Kiyoko Kawamura, Akemi Sakamoto, et al.. (2004). Impaired lymphocyte development and function in Clast5/Stra13/DEC1‐transgenic mice. European Journal of Immunology. 34(5). 1322–1332. 29 indexed citations
14.
Tada, Yuji, Jiyang O‐Wang, Yuichi Takiguchi, et al.. (2002). Cutting Edge: A Novel Role for Fas Ligand in Facilitating Antigen Acquisition by Dendritic Cells. The Journal of Immunology. 169(5). 2241–2245. 21 indexed citations
15.
Bahar, Rumana, Yanqing Wang, Kiyoko Kawamura, et al.. (2002). Clast5/Stra13 Is a Negative Regulator of B Lymphocyte Activation. Biochemical and Biophysical Research Communications. 292(1). 121–127. 32 indexed citations
16.
Tada, Yuji, Jiyang O‐Wang, Yuichi Takiguchi, et al.. (2002). T cell dependent and independent antitumor immunity generated by the expression of Fas ligand on mouse lung carcinoma cells. International Journal of Molecular Medicine. 9(3). 281–5. 4 indexed citations
17.
O‐Wang, Jiyang, Kenji Kawamura, Yuji Tada, et al.. (2001). DNA polymerase kappa, implicated in spontaneous and DNA damage-induced mutagenesis, is overexpressed in lung cancer.. PubMed. 61(14). 5366–9. 106 indexed citations
18.
Iwadate, Yasuo, Masatoshi Tagawa, Hiroki Namba, et al.. (2000). Immunological responsiveness to interleukin-2-producing brain tumors can be restored by concurrent subcutaneous transplantation of the same tumors. Cancer Gene Therapy. 7(9). 1263–1269. 6 indexed citations
19.
Takenaga, Keizo, Masatoshi Tagawa, & S Sakiyama. (1996). Therapeutic potency of transduction with herpes simplex virus thymidine kinase gene against multidrug resistant mouse leukemia cells.. PubMed. 16(2). 681–5. 4 indexed citations
20.
Taniguchi, Masaru, et al.. (1989). Syngeneic Monoclonal Antimelanoma Antibodies and Their Application for Analysis of Tumor Antigens, Gene Cloning, and In Vitro/In Vivo Diagnosis. Pigment Cell Research. 2(4). 254–258. 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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