Atsushi Wada
- Cell Biology top 10%
- Immunology top 10%
- Neutrophil, Myeloperoxidase and Oxidative Mechanisms 3
- Physiology top 10%
- Erythrocyte Function and Pathophysiology 4
- Immunology and Allergy top 10%
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- Sphingolipid Metabolism and Signaling 6
- Lipid Membrane Structure and Behavior 4
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- Lipoproteins and Cardiovascular Health 5
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- Cancer, Lipids, and Metabolism 5
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- Blood properties and coagulation 3
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- Hematopoietic Stem Cell Transplantation 3
- Co-authors
- Yasuyuki IgarashiYuri TakagiMari KonoDaniel L. BakerTakamitsu SanoGábor TigyiTetsuyuki KobayashiYutaka Yatomi
- 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
- Cell Biology 183
- Immunology 225
- Physiology 254
- Immunology and Allergy 57
- Molecular Biology 575
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
The 25 scholars most cited alongside Atsushi Wada, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 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. | 2017 | 1 |
| 3 | 2017 | 10 | |
| 4 | 2015 | 7 | |
| 5 | 2015 | 40 | |
| 6 | 2012 | 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 | 2011 | 1 |
| 8 | 2011 | 1 | |
| 9 | 2011 | 1 | |
| 10 | 2009 | 38 | |
| 11 | 2006 | 7 | |
| 12 | 2003 | 50 | |
| 13 | 2002 | 220 | |
| 14 | 2002 | 31 | |
| 15 | 2002 | 37 | |
| 16 | 2001 | 58 | |
| 17 | 2000 | 25 | |
| 18 | 1994 | 9 | |
| 19 | 1993 | 13 | |
| 20 | 1988 | 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), Cancer, Lipids, and Metabolism (5 papers), Erythrocyte Function and Pathophysiology (4 papers), Lipid Membrane Structure and Behavior (4 papers), Blood properties and coagulation (3 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (3 papers) and Hematopoietic Stem Cell Transplantation (3 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.
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.