M. Seki

3.9k citations
58 papers · 1.1k · h-index 18

Impact in

Papers in

M. Seki

54 papers receiving 1.1k citations

Peers

M. Seki
Comparison fields: 5 of 129
  • Nuclear and High Energy Physics 160
  • Computer Vision and Pattern Recognition 207
  • Aging 17
  • Business and International Management 18
  • Molecular Biology 348
Replace Liang Gao with:
Liang Gao United States
Sheng Liu China
Satoshi Ito Japan
Weimin Shen China
Bernd Schäfer Germany
И. В. Семенова Russia
Yusuke Nakamura Japan
Pascuala Garcı́a-Martı́nez Spain
Hongguang Wang China
Juan M. Bueno Spain
M. Seki relative to Liang Gao United States Liang Gao's profile →
Citations per field
00.5×8.5×
Liang Gao · 1×
Citations per year

Countries citing papers authored by M. Seki

Since Specialization
Citations

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

Fields of papers citing papers by M. Seki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020151
2 2003142
3 197876
4 202074
5 200262
6 201049
7 202046
8 199645
9 200043
10 197832
11 200431
12 199029
13 199128
14 198925
15 199121
16 199021
17 202120
18 197920
19 200516
20 199216

About M. Seki

M. Seki is a scholar working on Molecular Biology, Materials Chemistry, Aerospace Engineering, Nuclear and High Energy Physics and Surgery, having authored 58 papers that have together received 1.1k indexed citations. Recurring topics across this work include Fusion materials and technologies (14 papers), Magnetic confinement fusion research (10 papers), CRISPR and Genetic Engineering (6 papers), Nuclear Materials and Properties (5 papers), Superconducting Materials and Applications (5 papers), Nuclear reactor physics and engineering (4 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (4 papers) and Laser-Plasma Interactions and Diagnostics (4 papers). The work is most often cited by research in Nuclear and High Energy Physics (160 citations), Computer Vision and Pattern Recognition (207 citations), Aging (17 citations), Business and International Management (18 citations) and Molecular Biology (348 citations). M. Seki has collaborated with scholars based in Japan, United States and Canada. Frequent co-authors include Kazuhiko Sumi, Hiroshi Kawamura, Takahiro Wada, Nozomu Yachie, Hiroyuki Aburatani, O. Naito, Takao Fujita, S. Ide, Christian R. Landry and Philippe C Després. Their work appears in journals such as Journal of Nuclear Materials, Nuclear Fusion, Fusion Engineering and Design, Scientific Reports and Nature Biotechnology.

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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