Masami Ikeda

1.5k citations
72 papers · 1.2k · h-index 16

Impact in

  • Immunology top 10%
    • Invertebrate Immune Response Mechanisms
    • Aquaculture disease management and microbiota
    • Machine Learning in Bioinformatics
    • RNA and protein synthesis mechanisms
    • Genomics and Phylogenetic Studies

Papers in

Masami Ikeda

70 papers receiving 1.2k citations

Peers

Masami Ikeda
Comparison fields: 5 of 121
  • Immunology 204
  • Molecular Biology 491
  • Materials Chemistry 242
  • Astronomy and Astrophysics 84
  • Microbiology 29
Replace Christopher Osgood with:
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Olga N. Pakhomova United States
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Citations per field
00.5×10×14×
Christopher Osgood · 1×
Citations per year

Countries citing papers authored by Masami Ikeda

Since Specialization
Citations

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

Fields of papers citing papers by Masami Ikeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003238
2 2004175
3
Transmembrane topology prediction methods: a re-assessment and improvement by a consensus method using a dataset of experimentally-characterized transmembrane topologies.
2002115
4 200385
5 197241
6 200240
7 200334
8 200333
9 201132
10 198132
11 200428
12 198222
13 200419
14 198718
15 201118
16 198818
17 198214
18
Structure Design of Neural Networks Using Genetic Algorithms.
200113
19 198112
20 199612

About Masami Ikeda

Masami Ikeda is a scholar working on Electrical and Electronic Engineering, Materials Chemistry, Molecular Biology, Control and Systems Engineering and Mechanical Engineering, having authored 72 papers that have together received 1.2k indexed citations. Recurring topics across this work include High voltage insulation and dielectric phenomena (26 papers), Power Transformer Diagnostics and Insulation (24 papers), Machine Learning in Bioinformatics (15 papers), RNA and protein synthesis mechanisms (12 papers), Thermal Analysis in Power Transmission (12 papers), Genomics and Phylogenetic Studies (8 papers), Non-Destructive Testing Techniques (5 papers) and Lightning and Electromagnetic Phenomena (4 papers). The work is most often cited by research in Immunology (204 citations), Molecular Biology (491 citations), Materials Chemistry (242 citations), Astronomy and Astrophysics (84 citations) and Microbiology (29 citations). Masami Ikeda has collaborated with scholars based in Japan, United States and Italy. Frequent co-authors include Toshio Shimizu, Masafumi Arai, Masanobu Satake, Toru Kikuchi, H. Ōkubo, Masaki Honda, Yoshihiro Kawaguchi, Nori Satoh, Maria Rosaria Pinto and Daniel S. Rokhsar. Their work appears in journals such as IEEE Transactions on Power Delivery, Bioscience Biotechnology and Biochemistry, Proceedings Genome Informatics Workshop/Genome informatics, Nucleic Acids Research and IEEJ Transactions on Power and Energy.

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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