TL Que
Impact in
- Agronomy and Crop Science top 2%
- Animal Disease Management and Epidemiology
- Infectious Diseases top 5%
- Viral gastroenteritis research and epidemiology
- Viral Infections and Vectors
- SARS-CoV-2 and COVID-19 Research
Papers in
-
- Influenza Virus Research Studies 1
-
- Viral gastroenteritis research and epidemiology 2
- Antimicrobial Resistance in Staphylococcus 1
- Co-authors
- Paul K.S. Chan (1 shared paper)Rita Yn Tz Sung (1 shared paper)Malik Peiris (1 shared paper)Dnc Tsang (2 shared papers)Kwok‐Yung Yuen (2 shared papers)Pak‐Leung Ho (3 shared papers)River Chun‐Wai Wong (1 shared paper)WH Seto (1 shared paper)
- Journals
- The Lancet (1 paper)Hong Kong Journal of Emergency Medicine (1 paper)Laboratory Medicine (1 paper)The HKU Scholars Hub (University of Hong Kong) (1 paper)PubMed (1 paper)
In The Last Decade
TL Que
4 papers receiving 785 citations
TL Que's Hit Papers
Peers
Comparison fields: 5 of 71
- Agronomy and Crop Science 268
- Infectious Diseases 421
- Epidemiology 700
- Modeling and Simulation 42
- Immunology 149
Countries citing papers authored by TL Que
This map shows the geographic impact of TL Que'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 TL Que with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites TL Que more than expected).
Fields of papers citing papers by TL Que
This network shows the impact of papers produced by TL Que. 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 TL Que. The network helps show where TL Que may publish in the future.
Co-authors
The 11 scholars most cited alongside TL Que, 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 | Clinical features and rapid viral diagnosis of human disease associated with avian influenza A H5N1 virus Hit paper breakdown → | 1998 | 814 |
| 2 | 2011 | 3 | |
| 3 | Molecular epidemiology of community-associated methicillin-resistant Staphylococcus aureus. | 2009 | 1 |
| 4 | Rapid rise of fluoroquinolone resistance among Streptococcus pneumoniae in Hong Kong linked to acquisition of fluoroquinolone resistance by the locally dominant Spanish 23F clone | 2001 | 1 |
| 5 | 2010 | 1 |
About TL Que
TL Que is a scholar working on Epidemiology, Infectious Diseases, Molecular Biology, Pharmacology and Clinical Biochemistry, having authored 5 papers that have together received 820 indexed citations. Recurring topics across this work include Viral gastroenteritis research and epidemiology (2 papers), Antibiotics Pharmacokinetics and Efficacy (1 paper), Influenza Virus Research Studies (1 paper), Antimicrobial Resistance in Staphylococcus (1 paper), Antibiotic Resistance in Bacteria (1 paper), Animal Disease Management and Epidemiology (1 paper), Molecular Biology Techniques and Applications (1 paper) and Vibrio bacteria research studies (1 paper). The work is most often cited by research in Agronomy and Crop Science (268 citations), Infectious Diseases (421 citations), Epidemiology (700 citations), Modeling and Simulation (42 citations) and Immunology (149 citations). TL Que has collaborated with scholars based in Hong Kong and China. Frequent co-authors include Paul K.S. Chan, Rita Yn Tz Sung, Malik Peiris, Dnc Tsang, Kwok‐Yung Yuen, Pak‐Leung Ho, River Chun‐Wai Wong, WH Seto, Eugene Lai and TK Ng. Their work appears in journals such as The Lancet, Hong Kong Journal of Emergency Medicine, Laboratory Medicine, The HKU Scholars Hub (University of Hong Kong) and PubMed.
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.