Kenichi Tamama

3.3k citations
46 papers · 2.7k indexed · 1 hit paper · h-index 25
Topics
Mesenchymal stem cell research (15 papers)Tissue Engineering and Regenerative Medicine (8 papers)Sphingolipid Metabolism and Signaling (8 papers)
Journals
Journal of Biological ChemistrySHILAP Revista de lepidopterologíaBiochemical Journal
Partner nations
United StatesJapanChina

In The Last Decade

Kenichi Tamama

46 papers receiving 2.6k citations

Hit Papers

Spheroid Culture of Mesenchymal Stem Cells20152026201820222015100200300

Peers

Kenichi Tamama
Comparison fields: 5 of 124
  • Molecular Biology 1.3k
  • Genetics 720
  • Surgery 712
  • Biomedical Engineering 481
  • Biomaterials 435
Replace Virginia Tirino with:
Virginia Tirino Italy
Ólafur E. Sigurjónsson Iceland
Vincenzo Desiderio Italy
Sang‐Mo Kwon South Korea
Karim Boumédiene France
Rosa Maria Borzı̀ Italy
Augusto Pessina Italy
Qunzhou Zhang United States
Feng Lu China
Kenichi Tamama relative to Virginia Tirino Italy Virginia Tirino's profile →
Citations per field
00.5×1.5×
Virginia Tirino · 1×
Citations per year

Countries citing papers authored by Kenichi Tamama

Since Specialization
Citations

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

Fields of papers citing papers by Kenichi Tamama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kenichi Tamama

This figure shows the co-authorship network connecting the top 25 collaborators of Kenichi Tamama. A scholar is included among the top collaborators of Kenichi Tamama based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kenichi Tamama. Kenichi Tamama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 4
2 28
3 10
4 39
5 1
6 19
7 48
8 24
9
Spheroid Culture of Mesenchymal Stem Cellsbreakdown →
374
10 52
11 14
12 47
13 77
14 10
15 88
16 59
17 4
18 45
19 7
20 187

About Kenichi Tamama

Kenichi Tamama is a scholar working on Toxicology, Genetics and Biomaterials, having authored 46 papers that have together received 2.7k indexed citations. Recurring topics across this work include Mesenchymal stem cell research (15 papers), Tissue Engineering and Regenerative Medicine (8 papers) and Sphingolipid Metabolism and Signaling (8 papers). The work is most often cited by research in Genetics (720 citations), Biomaterials (435 citations) and Cell Biology (433 citations). Kenichi Tamama has collaborated with scholars based in United States, Japan and China. Frequent co-authors include Alan Wells, Fumikazu Okajima, Takao Kimura, Jianjun Guan, Atsushi Kuwabara, Kōichi Sato, Hideaki Tomura, Chandan K. Sen, Linda G. Griffith and Haruhisa Kawasaki. Their work appears in journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Biochemical Journal.

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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