K. Maeno

1.2k citations
52 papers · 930 · h-index 16

Impact in

  • Epidemiology top 10%
    • Herpesvirus Infections and Treatments
    • Virology and Viral Diseases
    • Cytomegalovirus and herpesvirus research
    • Influenza Virus Research Studies
  • Virology top 10%

Papers in

    • Influenza Virus Research Studies 11
    • Virology and Viral Diseases 9
    • Herpesvirus Infections and Treatments 8

K. Maeno

50 papers receiving 873 citations

Peers

K. Maeno
Comparison fields: 5 of 98
  • Epidemiology 451
  • Virology 44
  • Animal Science and Zoology 72
  • Computer Vision and Pattern Recognition 138
  • Genetics 185
Replace Michael Tigges with:
Michael Tigges United States
Daniel B. Sheffer United States
T. Whitbread Australia
Thomas Fletcher United States
P. Thévenet France
Rolando Estrada United States
Klaus‐Peter Pleißner Germany
T. Nakamura Japan
Jiong Wang China
Rüdiger Braun Germany
K. Maeno relative to Michael Tigges United States Michael Tigges's profile →
Citations per field
00.5×4.8×
Michael Tigges · 1×
Citations per year

Countries citing papers authored by K. Maeno

Since Specialization
Citations

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

Fields of papers citing papers by K. Maeno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside K. Maeno, 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 K. Maeno Line = papers co-authored together K. Maeno links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201798
2 200696
3 197978
4 199174
5 198763
6 198348
7 199338
8 200338
9 200329
10 199328
11 199126
12 198221
13 198219
14 198718
15 198717
16 197115
17 198515
18 200515
19 197815
20 201513

About K. Maeno

K. Maeno is a scholar working on Epidemiology, Immunology, Infectious Diseases, Computational Mechanics and Molecular Biology, having authored 52 papers that have together received 930 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (11 papers), Virology and Viral Diseases (9 papers), Herpesvirus Infections and Treatments (8 papers), Computational Fluid Dynamics and Aerodynamics (7 papers), Animal Virus Infections Studies (6 papers), Gas Dynamics and Kinetic Theory (6 papers), Laser-Plasma Interactions and Diagnostics (6 papers) and Virus-based gene therapy research (5 papers). The work is most often cited by research in Epidemiology (451 citations), Virology (44 citations), Animal Science and Zoology (72 citations), Computer Vision and Pattern Recognition (138 citations) and Genetics (185 citations). K. Maeno has collaborated with scholars based in Japan, United States and Singapore. Frequent co-authors include Yukihiro Nishiyama, Tatsuya Tsurumi, Qibin Sun, Shih-Fu Chang, Kaoru Shimokata, Masao Iinuma, T Matsumoto, Yoshinori Nagai, Tetsuya Yoshida and Yasuhiko Ito. Their work appears in journals such as Journal of General Virology, Archives of Virology, Infection and Immunity, Shock Waves and Journal of Virology.

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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