Nay Win

2.4k citations
55 papers · 1.5k · h-index 19

Impact in

Papers in

    • Blood groups and transfusion 39
    • Platelet Disorders and Treatments 5
    • Erythrocyte Function and Pathophysiology 22

Nay Win

53 papers receiving 1.5k citations

Peers

Nay Win
Comparison fields: 5 of 75
  • Biochemistry 551
  • Hematology 980
  • Genetics 680
  • Critical Care and Intensive Care Medicine 275
  • Management of Technology and Innovation 213
Replace G. D. Poole with:
G. D. Poole United Kingdom
D Rafanelli Italy
S.J. Stanworth United Kingdom
Ben Saxon Australia
H. Hambley United Kingdom
S. Seidl Germany
Gunilla Kumlien Sweden
Ulrik Sprogøe Denmark
Daniel B. Brubaker United States
S. Bryant United States
Nay Win relative to G. D. Poole United Kingdom G. D. Poole's profile →
Citations per field
00.5×8.8×
G. D. Poole · 1×
Citations per year

Countries citing papers authored by Nay Win

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Nay Win Line = papers co-authored together Nay Win links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009268
2 2012128
3 200891
4 200188
5 201678
6 201678
7 200873
8 199565
9 200963
10 200143
11 200041
12 200040
13 200439
14 200934
15 201130
16 200429
17 200725
18 199722
19 201920
20 200018

About Nay Win

Nay Win is a scholar working on Hematology, Physiology, Genetics, Biochemistry and Genetics, having authored 55 papers that have together received 1.5k indexed citations. Recurring topics across this work include Blood groups and transfusion (39 papers), Erythrocyte Function and Pathophysiology (22 papers), Hemoglobinopathies and Related Disorders (19 papers), Blood transfusion and management (12 papers), Blood disorders and treatments (11 papers), Platelet Disorders and Treatments (5 papers), Respiratory viral infections research (5 papers) and Blood donation and transfusion practices (4 papers). The work is most often cited by research in Biochemistry (551 citations), Hematology (980 citations), Genetics (680 citations), Critical Care and Intensive Care Medicine (275 citations) and Management of Technology and Innovation (213 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, Elizabeth M. Love, Louise Choo, D. Stainsby and Hannah Cohen. Their work appears in journals such as Vox Sanguinis, Transfusion, 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.

Explore authors with similar magnitude of impact