Eiichi Soeda

2.1k citations
46 papers · 1.6k indexed · 2 hit papers · h-index 19

Impact in

  • Immunology top 10%
    • T-cell and B-cell Immunology
  • Oncology top 10%
    • Polyomavirus and related diseases

Papers in

Eiichi Soeda

45 papers receiving 1.4k citations

Hit Papers

Structure and physical map of 64 variable segments in the 3′ 0.8–megabase region of the human immunoglobulin heavy–chain locus 1993 · 276 citations
2761980202619952010100200300

Peers

Eiichi Soeda
Comparison fields: 5 of 91
  • Immunology 315
  • Oncology 397
  • Molecular Biology 830
  • Genetics 313
  • Genetics 112
Replace Leah Lipsich with:
Leah Lipsich United States
John M. Lehman United States
H L Ozer United States
Albert van Ooyen Netherlands
Diana Sheiness United States
Roger H. Kennett United States
Harvey L. Ozer United States
M P Calos United States
Jared L. Clever United States
Madeleine Cochet France
Eiichi Soeda relative to Leah Lipsich United States Leah Lipsich's profile →
Citations per field
00.5×4.3×
Leah Lipsich · 1×
Citations per year

Countries citing papers authored by Eiichi Soeda

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network

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.

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

All Works

20 of 20 papers shown
#Work
1 200115
2 2001132
3 200118
4 200126
5 1999108
6 19980
7 19988
8 199815
9 199721
10 199640
11 199589
12 199441
13 199425
14
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 →
1993276
15 19925
16 199114
17 19905
18 198930
19 19731
20 19681

About Eiichi Soeda

Eiichi Soeda is a scholar working on Developmental Biology, Virology, Molecular Biology, Genetics and Biotechnology, having authored 46 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), Genomics and Phylogenetic Studies (4 papers), CRISPR and Genetic Engineering (4 papers), Neuroblastoma Research and Treatments (4 papers), Genomic variations and chromosomal abnormalities (4 papers) and T-cell and B-cell Immunology (4 papers). The work is most often cited by research in Immunology (315 citations), Oncology (397 citations), Molecular Biology (830 citations), Genetics (313 citations) and Genetics (112 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, Yosho Fukita, Fumihiko Matsuda, Euy Kyun Shin, Ryusuke Matsumura, Hitoshi Nagaoka, Tasuku Honjo and Rakesh Anand. Their work appears in journals such as Genomics, Nucleic Acids Research, Nature, Nature Genetics 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.

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