Takuma Hayashi
- Molecular Biology top 10%
- Immunology top 5%
- Oncology top 10%
- Cancer Research top 10%
- Genetics top 10%
- Co-authors
- Denise L. FaustmanIkuo KonishiAkiko HoriuchiTanri ShiozawaShiro MaedaToshiyuki SekineTakashi OkamotoYasuhiko Iwamoto
- Topics
- Uterine Myomas and Treatments (18 papers)NF-κB Signaling Pathways (14 papers)Ovarian cancer diagnosis and treatment (12 papers)
- Journals
- Journal of Biological ChemistryNature MedicineSHILAP Revista de lepidopterología
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Takuma Hayashi
98 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 103
- Molecular Biology 755
- Immunology 453
- Oncology 279
- Cancer Research 276
- Genetics 255
Countries citing papers authored by Takuma Hayashi
This map shows the geographic impact of Takuma Hayashi'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 Takuma Hayashi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takuma Hayashi more than expected).
Fields of papers citing papers by Takuma Hayashi
This network shows the impact of papers produced by Takuma Hayashi. 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 Takuma Hayashi. The network helps show where Takuma Hayashi may publish in the future.
Co-authorship network of co-authors of Takuma Hayashi
This figure shows the co-authorship network connecting the top 25 collaborators of Takuma Hayashi. A scholar is included among the top collaborators of Takuma Hayashi 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 Takuma Hayashi. Takuma Hayashi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 10 | |
| 4 | 3 | |
| 5 | Diagnostic Biomarker Candidates Including NT5DC2 for Human Uterine Mesenchymal Tumors | 4 |
| 6 | 2 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | 10 | |
| 10 | 6 | |
| 11 | 1 | |
| 12 | 5 | |
| 13 | 2 | |
| 14 | A potential diagnostic biomarker: proteasome subunit LMP2/β1i-differential expression in human uterus neoplasm | 1 |
| 15 | 9 | |
| 16 | 43 | |
| 17 | 25 | |
| 18 | 66 | |
| 19 | 7 | |
| 20 | Clinical study of gatifloxacin in prostatitis | 0 |
About Takuma Hayashi
Takuma Hayashi is a scholar working on Obstetrics and Gynecology, Cancer Research and Reproductive Medicine, having authored 107 papers that have together received 1.7k indexed citations. Recurring topics across this work include Uterine Myomas and Treatments (18 papers), NF-κB Signaling Pathways (14 papers) and Ovarian cancer diagnosis and treatment (12 papers). The work is most often cited by research in Obstetrics and Gynecology (179 citations), Immunology (453 citations) and Cancer Research (276 citations). Takuma Hayashi has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Denise L. Faustman, Ikuo Konishi, Denise L. Faustman, Akiko Horiuchi, Tanri Shiozawa, Shiro Maeda, Toshiyuki Sekine, Takashi Okamoto, Yasuhiko Iwamoto and Kenji Sano. Their work appears in journals such as Journal of Biological Chemistry, Nature Medicine and SHILAP Revista de lepidopterología.
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.