Win Win Maw
Impact in
- Molecular Medicine top 10%
- Antibiotic Resistance in Bacteria
- Microbiology top 10%
- Reproductive tract infections research
Papers in
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- Tuberculosis Research and Epidemiology 3
- Antimicrobial Resistance in Staphylococcus 3
- Leprosy Research and Treatment 3
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- Bacterial biofilms and quorum sensing 5
- Co-authors
- Haruaki Tomioka (2 shared papers)Katsumasa Sato (3 shared papers)Katerina Achilleos (3 shared papers)Toshiaki Shimizu (4 shared papers)Hajime Saito (2 shared papers)Meiji Soe Aung (7 shared papers)Mark D. Williams (2 shared papers)Bhaskar Dasgupta (2 shared papers)
In The Last Decade
Win Win Maw
27 papers receiving 529 citations
Peers
Comparison fields: 5 of 88
- Molecular Medicine 65
- Microbiology 48
- Infectious Diseases 131
- Applied Microbiology and Biotechnology 12
- Rheumatology 79
Countries citing papers authored by Win Win Maw
This map shows the geographic impact of Win Win Maw'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 Win Win Maw with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Win Win Maw more than expected).
Fields of papers citing papers by Win Win Maw
This network shows the impact of papers produced by Win Win Maw. 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 Win Win Maw. The network helps show where Win Win Maw may publish in the future.
Co-authors
The 25 scholars most cited alongside Win Win Maw, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Fast track pathway reduces sight loss in giant cell arteritis: results of a longitudinal observational cohort study. | 2015 | 129 |
| 2 | 2017 | 56 | |
| 3 | 2006 | 52 | |
| 4 | 2012 | 51 | |
| 5 | 1995 | 45 | |
| 6 | 2018 | 41 | |
| 7 | 2016 | 24 | |
| 8 | 1997 | 16 | |
| 9 | 1996 | 14 | |
| 10 | 2001 | 13 | |
| 11 | 2000 | 11 | |
| 12 | 2017 | 11 | |
| 13 | 2019 | 11 | |
| 14 | 2022 | 11 | |
| 15 | 1996 | 9 | |
| 16 | 2019 | 8 | |
| 17 | 2019 | 7 | |
| 18 | 2020 | 6 | |
| 19 | 2023 | 5 | |
| 20 | 2014 | 4 |
About Win Win Maw
Win Win Maw is a scholar working on Infectious Diseases, Molecular Biology, Epidemiology, Immunology and Molecular Medicine, having authored 30 papers that have together received 537 indexed citations. Recurring topics across this work include Mycobacterium research and diagnosis (5 papers), Bacterial biofilms and quorum sensing (5 papers), Antibiotic Resistance in Bacteria (4 papers), Vasculitis and related conditions (3 papers), Tuberculosis Research and Epidemiology (3 papers), Antimicrobial Resistance in Staphylococcus (3 papers), Leprosy Research and Treatment (3 papers) and Immune Response and Inflammation (3 papers). The work is most often cited by research in Molecular Medicine (65 citations), Microbiology (48 citations), Infectious Diseases (131 citations), Applied Microbiology and Biotechnology (12 citations) and Rheumatology (79 citations). Win Win Maw has collaborated with scholars based in Japan, Myanmar and Thailand. Frequent co-authors include Haruaki Tomioka, Katsumasa Sato, Katerina Achilleos, Toshiaki Shimizu, Hajime Saito, Meiji Soe Aung, Mark D. Williams, Bhaskar Dasgupta, Christian Dejaco and Nobumichi Kobayashi. Their work appears in journals such as Microbial Drug Resistance, Clinical & Experimental Immunology, Journal of Leukocyte Biology, Lara D. Veeken and Pharmaceutical Biology.
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.