Nay Win
Impact in
- Biochemistry top 1%
- Blood transfusion and management
- Hematology top 1%
- Blood groups and transfusion
Papers in
- Hematology 36
- Blood groups and transfusion 33
- Physiology 17
- Erythrocyte Function and Pathophysiology 17
- Co-authors
- C. Chapman (3 shared papers)Geoff Lucas (3 shared papers)Edwin Massey (4 shared papers)Josu de la Fuente (2 shared papers)Cristina Navarrete (3 shared papers)Helen V. New (1 shared paper)Louise Choo (2 shared papers)Hannah Cohen (2 shared papers)
- Journals
- Transfusion (11 papers)Vox Sanguinis (11 papers)British Journal of Haematology (4 papers)Transfusion Medicine (4 papers)Viruses (4 papers)
- Partner nations
- United KingdomNigeriaJapan
In The Last Decade
Nay Win
56 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 72
- Biochemistry 502
- Hematology 896
- Genetics 560
- Critical Care and Intensive Care Medicine 216
- Physiology 443
Countries citing papers authored by Nay Win
This map shows the geographic impact of Nay Win'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 Nay Win with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nay Win more than expected).
Fields of papers citing papers by Nay Win
This network shows the impact of papers produced by Nay Win. 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 Nay Win. The network helps show where Nay Win may publish in the future.
Co-authors
The 25 scholars most cited alongside Nay Win, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 279 | |
| 2 | 2012 | 136 | |
| 3 | 2001 | 99 | |
| 4 | 2008 | 92 | |
| 5 | 2016 | 87 | |
| 6 | 2016 | 85 | |
| 7 | 2008 | 76 | |
| 8 | 1995 | 69 | |
| 9 | 2009 | 66 | |
| 10 | 2001 | 45 | |
| 11 | 2000 | 44 | |
| 12 | 2000 | 44 | |
| 13 | 2004 | 40 | |
| 14 | 2009 | 36 | |
| 15 | 2011 | 33 | |
| 16 | 1997 | 29 | |
| 17 | 2004 | 29 | |
| 18 | 2007 | 26 | |
| 19 | 2019 | 21 | |
| 20 | 1998 | 20 |
About Nay Win
Nay Win is a scholar working on Hematology, Physiology, Genetics, Biochemistry and Epidemiology, having authored 58 papers that have together received 1.6k indexed citations. Recurring topics across this work include Blood groups and transfusion (33 papers), Erythrocyte Function and Pathophysiology (17 papers), Hemoglobinopathies and Related Disorders (13 papers), Blood transfusion and management (11 papers), Blood disorders and treatments (8 papers), Respiratory viral infections research (4 papers), Trauma, Hemostasis, Coagulopathy, Resuscitation (3 papers) and Influenza Virus Research Studies (3 papers). The work is most often cited by research in Biochemistry (502 citations), Hematology (896 citations), Genetics (560 citations), Critical Care and Intensive Care Medicine (216 citations) and Physiology (443 citations). Nay Win has collaborated with scholars based in United Kingdom, Nigeria and Japan. Frequent co-authors include C. Chapman, Geoff Lucas, Edwin Massey, Josu de la Fuente, Cristina Navarrete, Helen V. New, Louise Choo, Hannah Cohen, Cliff Morgan and Shubha Allard. Their work appears in journals such as Transfusion, Vox Sanguinis, British Journal of Haematology, Transfusion Medicine and Viruses.
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.