Atsushi Wada
- Molecular Biology
- Physiology top 10%
- Immunology top 10%
- Cell Biology top 10%
- Surgery
- Co-authors
- Yasuyuki IgarashiYuri TakagiMari KonoDaniel L. BakerTakamitsu SanoGábor TigyiTetsuyuki KobayashiYutaka Yatomi
- Topics
- Sphingolipid Metabolism and Signaling (6 papers)Lipoproteins and Cardiovascular Health (5 papers)Cancer, Lipids, and Metabolism (5 papers)
- Cited by
- Cell BiologyImmunologyPhysiology
- Partner nations
- JapanUnited StatesGermany
In The Last Decade
Atsushi Wada
44 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 105
- Molecular Biology 575
- Physiology 254
- Immunology 225
- Cell Biology 183
- Surgery 171
Countries citing papers authored by Atsushi Wada
This map shows the geographic impact of Atsushi Wada'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 Atsushi Wada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Atsushi Wada more than expected).
Fields of papers citing papers by Atsushi Wada
This network shows the impact of papers produced by Atsushi Wada. 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 Atsushi Wada. The network helps show where Atsushi Wada may publish in the future.
Co-authorship network of co-authors of Atsushi Wada
This figure shows the co-authorship network connecting the top 25 collaborators of Atsushi Wada. A scholar is included among the top collaborators of Atsushi Wada 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 Atsushi Wada. Atsushi Wada is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | New Alert Message Settings for the XN-series Automated Hematology Analyzer Are Useful for Avoiding Falsely High WBC Counts and to Detect Specimens with Giant Platelets. | 1 |
| 3 | 10 | |
| 4 | 7 | |
| 5 | 40 | |
| 6 | 24 | |
| 7 | Abstract 12204: Long-Term Effect of Ezetimibe-Plus-Statin vs Double-Dose Statin on Low-Density Lipoprotein Cholesterol Lowering in Coronary Artery Disease Patients Pre-Treated with a Statin; Focus on Cholesterol Absorption and Synthesis | 1 |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 38 | |
| 11 | 7 | |
| 12 | 50 | |
| 13 | 220 | |
| 14 | 31 | |
| 15 | 37 | |
| 16 | 58 | |
| 17 | 25 | |
| 18 | 9 | |
| 19 | 13 | |
| 20 | 3 |
About Atsushi Wada
Atsushi Wada is a scholar working on Hematology, Cardiology and Cardiovascular Medicine and Physiology, having authored 45 papers that have together received 1.2k indexed citations. Recurring topics across this work include Sphingolipid Metabolism and Signaling (6 papers), Lipoproteins and Cardiovascular Health (5 papers) and Cancer, Lipids, and Metabolism (5 papers). The work is most often cited by research in Cell Biology (183 citations), Immunology (225 citations) and Physiology (254 citations). Atsushi Wada has collaborated with scholars based in Japan, United States and Germany. Frequent co-authors include Yasuyuki Igarashi, Yuri Takagi, Mari Kono, Daniel L. Baker, Takamitsu Sano, Gábor Tigyi, Tetsuyuki Kobayashi, Yutaka Yatomi, Tamás Virág and Takayuki Kohno. Their work appears in journals such as Journal of Biological Chemistry, Circulation and Journal of the American College of Cardiology.
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.