Bin Gotoh

3.3k citations
56 papers · 3.0k · h-index 28

Impact in

Papers in

Bin Gotoh

56 papers receiving 2.9k citations

Peers

Bin Gotoh
Comparison fields: 5 of 82
  • Epidemiology 1.7k
  • Infectious Diseases 961
  • Animal Science and Zoology 561
  • Immunology 843
  • Virology 181
Replace Sibylle Schneider‐Schaulies with:
Sibylle Schneider‐Schaulies Germany
Machiko Nishio Japan
Richard D. Barry Australia
Andrea Maisner Germany
Bernadette M. Dutia United Kingdom
Michael N. Teng United States
L. Prevec Canada
Anthony V. Nicola United States
Maxine L. Linial United States
Brian J. Willett United Kingdom
Bin Gotoh relative to Sibylle Schneider‐Schaulies Germany Sibylle Schneider‐Schaulies's profile →
Citations per field
00.5×1.5×1.8×
Sibylle Schneider‐Schaulies · 1×
Citations per year

Countries citing papers authored by Bin Gotoh

Since Specialization
Citations

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

Fields of papers citing papers by Bin Gotoh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Bin Gotoh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bin Gotoh Line = papers co-authored together Bin Gotoh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 56 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1993387
2 1987205
3 1989151
4 1989146
5 1990144
6 1999119
7 1992118
8 2017117
9 2002113
10 2000101
11 199294
12 200194
13 200392
14 200882
15 200182
16 200479
17 198878
18 199472
19 200260
20 201349

About Bin Gotoh

Bin Gotoh is a scholar working on Epidemiology, Infectious Diseases, Immunology, Genetics and Molecular Biology, having authored 56 papers that have together received 3.0k indexed citations. Recurring topics across this work include Virology and Viral Diseases (24 papers), interferon and immune responses (17 papers), Viral Infections and Vectors (16 papers), Respiratory viral infections research (12 papers), Virus-based gene therapy research (12 papers), Viral Infections and Immunology Research (6 papers), Animal Virus Infections Studies (5 papers) and Viral Infectious Diseases and Gene Expression in Insects (4 papers). The work is most often cited by research in Epidemiology (1.7k citations), Infectious Diseases (961 citations), Animal Science and Zoology (561 citations), Immunology (843 citations) and Virology (181 citations). Bin Gotoh has collaborated with scholars based in Japan, United States and Germany. Frequent co-authors include Takayuki Komatsu, Kenji Takeuchi, Junko Yokoo, Michinari Hamaguchi, Tetsuya Toyoda, Yoshiyuki Nagai, Noel M. Inocencio, Takemasa Sakaguchi, Yasuo Ohnishi and Yoshinori Kitagawa. Their work appears in journals such as Journal of Virology, FEBS Letters, Virology, The EMBO Journal and Medical Microbiology and Immunology.

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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