Toshihiro Takeda
- Molecular Biology top 5%
- Epidemiology top 1%
- Cardiology and Cardiovascular Medicine top 2%
- Cell Biology top 2%
- Immunology top 5%
- Co-authors
- Kinya OtsuShungo HikosoOsamu YamaguchiKazuhiko NishidaYasushi MatsumuraMasatsugu HoriAtsuko NakaiIsamu Mizote
- Topics
- Biomedical Text Mining and Ontologies (12 papers)Topic Modeling (9 papers)Signaling Pathways in Disease (9 papers)
- Cited by
- PhysiologyAgingEpidemiology
- Partner nations
- JapanUnited KingdomUnited States
In The Last Decade
Toshihiro Takeda
82 papers receiving 4.7k citations
Hit Papers
Peers
Comparison fields: 5 of 145
- Molecular Biology 2.4k
- Epidemiology 1.9k
- Cardiology and Cardiovascular Medicine 1.1k
- Cell Biology 595
- Immunology 549
Countries citing papers authored by Toshihiro Takeda
This map shows the geographic impact of Toshihiro Takeda'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 Toshihiro Takeda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Toshihiro Takeda more than expected).
Fields of papers citing papers by Toshihiro Takeda
This network shows the impact of papers produced by Toshihiro Takeda. 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 Toshihiro Takeda. The network helps show where Toshihiro Takeda may publish in the future.
Co-authorship network of co-authors of Toshihiro Takeda
This figure shows the co-authorship network connecting the top 25 collaborators of Toshihiro Takeda. A scholar is included among the top collaborators of Toshihiro Takeda 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 Toshihiro Takeda. Toshihiro Takeda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 0 | |
| 4 | 5 | |
| 5 | 0 | |
| 6 | 8 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 6 | |
| 10 | A pre-training technique to localize medical BERT and enhance BioBERT. | 7 |
| 11 | 2 | |
| 12 | 3 | |
| 13 | 2 | |
| 14 | 2 | |
| 15 | 26 | |
| 16 | 35 | |
| 17 | FRS-074 Overexpression of Mitochondrial Peroxiredoxin-3 Ameliorates Left Ventricular Remodeling and Failure after Myocardial Infarction in Mice(Heart Failure Research (M) FRS15,Featured Research Session,The 70th Anniversary Annual Scientific Meeting of the Japanese Circulation Society) | 2 |
| 18 | High Sensitive C-Reacting Protein, Fibrinogen, White Blood Cell and the Recurrences of Cardiovascular Diseases on Five-Year Follow-Up of PCS Study | 1 |
| 19 | スタチン類やアスピリン,アンギオテンシンII修飾剤などで処置された患者の高感受性C-反応性蛋白レベルの違い | 9 |
| 20 | 30 |
About Toshihiro Takeda
Toshihiro Takeda is a scholar working on Health Information Management, Toxicology and Issues, ethics and legal aspects, having authored 92 papers that have together received 4.7k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (12 papers), Topic Modeling (9 papers) and Signaling Pathways in Disease (9 papers). The work is most often cited by research in Physiology (276 citations), Aging (99 citations) and Epidemiology (1.9k citations). Toshihiro Takeda has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Kinya Otsu, Shungo Hikoso, Osamu Yamaguchi, Kazuhiko Nishida, Yasushi Matsumura, Masatsugu Hori, Atsuko Nakai, Isamu Mizote, Takafumi Oka and Shigemiki Omiya. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.
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.