Eiichi Soeda
Impact in
- Oncology top 5%
- Polyomavirus and related diseases
- Immunology top 10%
- T-cell and B-cell Immunology
Papers in
-
- Glycosylation and Glycoproteins Research 4
- Genomics and Phylogenetic Studies 4
- Genetics 11
- Genomic variations and chromosomal abnormalities 4
- Co-authors
- Beverly E. Griffin (4 shared papers)John R. Arrand (3 shared papers)Nina Smolar (1 shared paper)Hitoshi Nagaoka (3 shared papers)Rakesh Anand (3 shared papers)Yosho Fukita (3 shared papers)Fumihiko Matsuda (3 shared papers)Euy Kyun Shin (3 shared papers)
- Journals
- Genomics (10 papers)Nucleic Acids Research (4 papers)Nature (3 papers)Review of Scientific Instruments (2 papers)Immunogenetics (2 papers)
- Partner nations
- JapanUnited KingdomUnited States
In The Last Decade
Eiichi Soeda
46 papers receiving 1.5k citations
Eiichi Soeda's Hit Papers
Peers
Comparison fields: 5 of 89
- Oncology 404
- Immunology 323
- Molecular Biology 834
- Genetics 318
- Genetics 111
Countries citing papers authored by Eiichi Soeda
This map shows the geographic impact of Eiichi Soeda'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 Eiichi Soeda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eiichi Soeda more than expected).
Fields of papers citing papers by Eiichi Soeda
This network shows the impact of papers produced by Eiichi Soeda. 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 Eiichi Soeda. The network helps show where Eiichi Soeda may publish in the future.
Co-authors
The 25 scholars most cited alongside Eiichi Soeda, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1980 | 351 | |
| 2 | Structure and physical map of 64 variable segments in the 3′ 0.8–megabase region of the human immunoglobulin heavy–chain locus Hit paper breakdown → | 1993 | 290 |
| 3 | 2001 | 140 | |
| 4 | 1999 | 110 | |
| 5 | 1995 | 91 | |
| 6 | 1984 | 59 | |
| 7 | 1980 | 55 | |
| 8 | 1994 | 41 | |
| 9 | 1996 | 40 | |
| 10 | 1978 | 40 | |
| 11 | 2006 | 36 | |
| 12 | 1989 | 31 | |
| 13 | 1984 | 28 | |
| 14 | 1980 | 27 | |
| 15 | 1994 | 27 | |
| 16 | 2001 | 26 | |
| 17 | 2000 | 26 | |
| 18 | 1997 | 22 | |
| 19 | 1977 | 21 | |
| 20 | 2001 | 18 |
About Eiichi Soeda
Eiichi Soeda is a scholar working on Molecular Biology, Genetics, Plant Science, Ecology and Immunology, having authored 47 papers that have together received 1.6k indexed citations. Recurring topics across this work include Bacteriophages and microbial interactions (8 papers), Polyomavirus and related diseases (6 papers), Plant Virus Research Studies (5 papers), Glycosylation and Glycoproteins Research (4 papers), Neuroblastoma Research and Treatments (4 papers), T-cell and B-cell Immunology (4 papers), Genomic variations and chromosomal abnormalities (4 papers) and Genomics and Phylogenetic Studies (4 papers). The work is most often cited by research in Oncology (404 citations), Immunology (323 citations), Molecular Biology (834 citations), Genetics (318 citations) and Genetics (111 citations). Eiichi Soeda has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Beverly E. Griffin, John R. Arrand, Nina Smolar, Hitoshi Nagaoka, Rakesh Anand, Yosho Fukita, Fumihiko Matsuda, Euy Kyun Shin, Takashi Imai and Makoto Haino. Their work appears in journals such as Genomics, Nucleic Acids Research, Nature, Review of Scientific Instruments and Immunogenetics.
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.