Tomomasa Matsuyama

1.6k total citations
76 papers, 1.2k citations indexed

About

Tomomasa Matsuyama is a scholar working on Immunology, Ecology and Molecular Biology. According to data from OpenAlex, Tomomasa Matsuyama has authored 76 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Immunology, 20 papers in Ecology and 15 papers in Molecular Biology. Recurrent topics in Tomomasa Matsuyama's work include Aquaculture disease management and microbiota (48 papers), Animal Virus Infections Studies (12 papers) and Vibrio bacteria research studies (10 papers). Tomomasa Matsuyama is often cited by papers focused on Aquaculture disease management and microbiota (48 papers), Animal Virus Infections Studies (12 papers) and Vibrio bacteria research studies (10 papers). Tomomasa Matsuyama collaborates with scholars based in Japan, United States and Taiwan. Tomomasa Matsuyama's co-authors include Takaji Iida, Chihaya Nakayasu, Takashi Kamaishi, Tomokazu Takano, Takamitsu Sakai, Norihisa Oseko, Motohiko Sano, Atushi Fujiwara, Jun Kurita and Takafumi Ito and has published in prestigious journals such as Blood, PLoS ONE and Scientific Reports.

In The Last Decade

Tomomasa Matsuyama

71 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tomomasa Matsuyama Japan 20 830 274 243 200 171 76 1.2k
Chihaya Nakayasu Japan 20 1.0k 1.3× 178 0.6× 288 1.2× 151 0.8× 260 1.5× 81 1.3k
Tomokazu Takano Japan 20 1.1k 1.3× 220 0.8× 187 0.8× 155 0.8× 186 1.1× 65 1.3k
Wes Baumgartner United States 18 610 0.7× 213 0.8× 250 1.0× 144 0.7× 218 1.3× 69 1.2k
Zaohe Wu China 22 1.0k 1.2× 338 1.2× 153 0.6× 230 1.1× 209 1.2× 68 1.3k
Jun-ichi Hikima Japan 27 1.7k 2.1× 441 1.6× 180 0.7× 126 0.6× 354 2.1× 89 2.1k
Junjie Bai China 21 736 0.9× 365 1.3× 126 0.5× 134 0.7× 367 2.1× 89 1.3k
Daniela Gómez United States 15 1.5k 1.8× 381 1.4× 278 1.1× 108 0.5× 412 2.4× 25 1.9k
M F McLoughlin United Kingdom 22 886 1.1× 144 0.5× 237 1.0× 207 1.0× 303 1.8× 39 1.3k
Lanjie Liao China 23 1.1k 1.3× 633 2.3× 244 1.0× 46 0.2× 304 1.8× 94 1.7k
Roberto Bermúdez Spain 22 682 0.8× 170 0.6× 283 1.2× 56 0.3× 250 1.5× 64 1.2k

Countries citing papers authored by Tomomasa Matsuyama

Since Specialization
Citations

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

Fields of papers citing papers by Tomomasa Matsuyama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomomasa Matsuyama

This figure shows the co-authorship network connecting the top 25 collaborators of Tomomasa Matsuyama. A scholar is included among the top collaborators of Tomomasa Matsuyama 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 Tomomasa Matsuyama. Tomomasa Matsuyama 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.
Matsuyama, Tomomasa, Satoshi Miwa, Tohru Mekata, et al.. (2024). A novel birnavirus identified as the causative agent of summer atrophy of pearl oyster (Pinctada fucata (Gould)). PeerJ. 12. e17321–e17321. 2 indexed citations
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Matsuura, Yuta, et al.. (2023). Dynamics of serum IgM level during the growth of juvenile Japanese amberjack Seriola quinqueradiata. Fisheries Science. 90(1). 65–74. 1 indexed citations
5.
Matsuyama, Tomomasa, Satoshi Miwa, Tohru Mekata, et al.. (2021). Mass mortality of pearl oyster ( Pinctada fucata (Gould)) in Japan in 2019 and 2020 is caused by an unidentified infectious agent. PeerJ. 9. e12180–e12180. 8 indexed citations
6.
Matsuura, Yuta, et al.. (2020). Development of a method to quantify endogenous IFNγ protein in amberjack species. Fish & Shellfish Immunology. 107(Pt A). 251–259. 2 indexed citations
7.
Matsuura, Yuta, et al.. (2019). Current status of fish vaccines in Japan. Fish & Shellfish Immunology. 95. 236–247. 36 indexed citations
8.
Takano, Tomokazu, Yoji Nakamura, Tomomasa Matsuyama, et al.. (2017). Complete Genome Sequence of Ichthyobacterium seriolicida JBKA-6 T , Isolated from Yellowtail (Seriola quinqueradiata) Affected by Bacterial Hemolytic Jaundice. Genome Announcements. 5(6). 3 indexed citations
9.
Kurata, Osamu, Shinpei Wada, Tomomasa Matsuyama, Takamitsu Sakai, & Tomokazu Takano. (2014). N-terminal region is responsible for chemotaxis-inducing activity of flounder IL-8. Fish & Shellfish Immunology. 38(2). 361–366. 10 indexed citations
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Kato, Goshi, Tomokazu Takano, Takamitsu Sakai, Tomomasa Matsuyama, & Chihaya Nakayasu. (2013). Vibrio anguillarum bacterin uptake via the gills of Japanese flounder and subsequent immune responses. Fish & Shellfish Immunology. 35(5). 1591–1597. 36 indexed citations
12.
Kato, Go, et al.. (2013). Antigenic proteins of Flavobacterium psychrophilum recognized by ayu Plecoglossus altivelis antisera. Diseases of Aquatic Organisms. 108(2). 103–112. 6 indexed citations
13.
Kurata, Osamu, et al.. (2010). Lymphocytes with T-cell-like properties express the Fas ligand in the Japanese flounder Paralichthys olivaceus. Fish & Shellfish Immunology. 30(2). 509–514. 16 indexed citations
14.
Sakai, Takamitsu, Tomomasa Matsuyama, Motohiko Sano, & Takaji Iida. (2009). Identification of novel putative virulence factors, adhesin AIDA and type VI secretion system, in atypical strains of fish pathogenicEdwardsiella tardaby genomic subtractive hybridization. Microbiology and Immunology. 53(3). 131–139. 19 indexed citations
15.
Matsuyama, Tomomasa, Atushi Fujiwara, Takamitsu Sakai, & Chihaya Nakayasu. (2008). Molecular cloning and expression analysis of interferon gamma gene in Japanese flounder Paralichthys olivaceus. Fisheries Science. 75(1). 253–255. 14 indexed citations
16.
Matsuyama, Tomomasa, Takashi Kamaishi, & Norihisa Oseko. (2006). Rapid Discrimination of Fish Pathogenic Vibrio and Photobacterium Species by Oligonucleotide DNA Array. Fish Pathology. 41(3). 105–112. 7 indexed citations
17.
Ito, Satoko, et al.. (2006). Virus-like particles associated with mass mortalities of the pen shell Atrina pectinata in Japan. Diseases of Aquatic Organisms. 71(2). 169–173. 21 indexed citations
18.
Matsuyama, Tomomasa, Atushi Fujiwara, Chihaya Nakayasu, et al.. (2006). Gene expression of leucocytes in vaccinated Japanese flounder (Paralichthys olivaceus) during the course of experimental infection with Edwardsiella tarda. Fish & Shellfish Immunology. 22(6). 598–607. 47 indexed citations
19.
Kamaishi, Takashi, Yutaka Fukuda, Hidemasa Kawakami, et al.. (2005). Identification and Pathogenicity of Intracellular Francisella Bacterium in Three-line Grunt Parapristipoma trilineatum. Fish Pathology. 40(2). 67–71. 64 indexed citations
20.
Matsuyama, Tomomasa & Takaji Iida. (1999). Comparison of Inflammatory and Peripheral Neutrophils of Carp and Tilapia in Defense Activities.. Fish Pathology. 34(1). 45–46. 6 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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