Un‐In Wu
Impact in
- Molecular Medicine top 2%
- Antibiotic Resistance in Bacteria
Papers in ⓘ
- Co-authors
- Steven M. Holland (5 shared papers)Shan‐Chwen Chang (32 shared papers)Wang‐Huei Sheng (21 shared papers)Yee‐Chun Chen (30 shared papers)Hung‐Ming Chang (6 shared papers)Jann‐Tay Wang (20 shared papers)Chyn‐Tair Lan (4 shared papers)Hsin‐Yun Sun (16 shared papers)
- Journals
- Journal of Microbiology Immunology and Infection (6 papers)International Journal of Infectious Diseases (4 papers)Journal of Pineal Research (3 papers)Applied Surface Science (3 papers)Clinical Microbiology and Infection (3 papers)
- Partner nations
- TaiwanUnited StatesUnited Kingdom
In The Last Decade
Un‐In Wu
59 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 126
- Molecular Medicine 172
- Applied Microbiology and Biotechnology 65
- Infectious Diseases 490
- Microbiology 15
- Endocrine and Autonomic Systems 133
Countries citing papers authored by Un‐In Wu
This map shows the geographic impact of Un‐In Wu'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 Un‐In Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Un‐In Wu more than expected).
Fields of papers citing papers by Un‐In Wu
This network shows the impact of papers produced by Un‐In Wu. 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 Un‐In Wu. The network helps show where Un‐In Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Un‐In Wu, 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 60 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 176 | |
| 2 | 2017 | 100 | |
| 3 | 2009 | 93 | |
| 4 | 2015 | 91 | |
| 5 | 2015 | 51 | |
| 6 | 2017 | 49 | |
| 7 | 2008 | 44 | |
| 8 | 2010 | 43 | |
| 9 | 2015 | 41 | |
| 10 | 2009 | 40 | |
| 11 | 2007 | 37 | |
| 12 | 2019 | 35 | |
| 13 | 2019 | 34 | |
| 14 | 2010 | 30 | |
| 15 | 2011 | 27 | |
| 16 | 2021 | 25 | |
| 17 | 2017 | 24 | |
| 18 | 2018 | 23 | |
| 19 | 2011 | 21 | |
| 20 | 2017 | 21 |
About Un‐In Wu
Un‐In Wu is a scholar working on Microbiology, Applied Microbiology and Biotechnology, Infectious Diseases, Molecular Medicine and Epidemiology, having authored 60 papers that have together received 1.4k indexed citations. Recurring topics across this work include Mycobacterium research and diagnosis (18 papers), Antifungal resistance and susceptibility (11 papers), Fungal Infections and Studies (10 papers), Tuberculosis Research and Epidemiology (9 papers), Immunodeficiency and Autoimmune Disorders (7 papers), Infectious Diseases and Mycology (7 papers), Influenza Virus Research Studies (6 papers) and Antibiotic Resistance in Bacteria (6 papers). The work is most often cited by research in Molecular Medicine (172 citations), Applied Microbiology and Biotechnology (65 citations), Infectious Diseases (490 citations), Microbiology (15 citations) and Endocrine and Autonomic Systems (133 citations). Un‐In Wu has collaborated with scholars based in Taiwan, United States and United Kingdom. Frequent co-authors include Steven M. Holland, Shan‐Chwen Chang, Wang‐Huei Sheng, Yee‐Chun Chen, Hung‐Ming Chang, Jann‐Tay Wang, Chyn‐Tair Lan, Hsin‐Yun Sun, Yu‐Chung Chuang and Fu‐Der Mai. Their work appears in journals such as Journal of Microbiology Immunology and Infection, International Journal of Infectious Diseases, Journal of Pineal Research, Applied Surface Science and Clinical Microbiology and Infection.
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.