T. Yang
Impact in
- Virology top 1%
- HIV Research and Treatment
- Infectious Diseases top 2%
- HIV/AIDS drug development and treatment
- HIV/AIDS Research and Interventions
Papers in
-
- Macrophage Migration Inhibitory Factor 2
- Co-authors
- Donald J. Graham (1 shared paper)Lori J. Gabryelski (1 shared paper)J C Quintero (1 shared paper)H.L. Robbins (1 shared paper)Kathleen Squires (1 shared paper)William A. Schleif (1 shared paper)Emilio A. Emini (1 shared paper)Malathi Shivaprakash (1 shared paper)
- Journals
- Journal of Translational Medicine (1 paper)Journal of Medicinal Chemistry (1 paper)The FASEB Journal (1 paper)Journal of Biological Chemistry (1 paper)Nature (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
T. Yang
12 papers receiving 1.0k citations
T. Yang's Hit Papers
Peers
Comparison fields: 5 of 97
- Virology 603
- Infectious Diseases 701
- Hepatology 71
- Developmental Neuroscience 24
- Media Technology 41
Countries citing papers authored by T. Yang
This map shows the geographic impact of T. Yang'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 T. Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Yang more than expected).
Fields of papers citing papers by T. Yang
This network shows the impact of papers produced by T. Yang. 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 T. Yang. The network helps show where T. Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside T. Yang, 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 | In vivo emergence of HIV-1 variants resistant to multiple protease inhibitors Hit paper breakdown → | 1995 | 810 |
| 2 | 2012 | 57 | |
| 3 | 2022 | 57 | |
| 4 | 2024 | 51 | |
| 5 | 2009 | 30 | |
| 6 | 2012 | 27 | |
| 7 | 2023 | 17 | |
| 8 | 2024 | 9 | |
| 9 | 2019 | 8 | |
| 10 | 2024 | 8 | |
| 11 | 2023 | 4 | |
| 12 | 2025 | 1 | |
| 13 | 2025 | 0 | |
| 14 | 2026 | 0 |
About T. Yang
T. Yang is a scholar working on Immunology, Molecular Biology, Computer Vision and Pattern Recognition, Infectious Diseases and Nephrology, having authored 14 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (2 papers), Advanced Vision and Imaging (2 papers), Image and Signal Denoising Methods (2 papers), Macrophage Migration Inhibitory Factor (2 papers), Plant Water Relations and Carbon Dynamics (1 paper), Osteoarthritis Treatment and Mechanisms (1 paper), Metabolism and Genetic Disorders (1 paper) and Gout, Hyperuricemia, Uric Acid (1 paper). The work is most often cited by research in Virology (603 citations), Infectious Diseases (701 citations), Hepatology (71 citations), Developmental Neuroscience (24 citations) and Media Technology (41 citations). T. Yang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Donald J. Graham, Lori J. Gabryelski, J C Quintero, H.L. Robbins, Kathleen Squires, William A. Schleif, Emilio A. Emini, Malathi Shivaprakash, Paul Deutsch and Elizabeth Röth. Their work appears in journals such as Journal of Translational Medicine, Journal of Medicinal Chemistry, The FASEB Journal, Journal of Biological Chemistry and Nature.
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.