Brian Tsang
Impact in
- Molecular Biology top 5%
- RNA Research and Splicing
- RNA modifications and cancer
- RNA and protein synthesis mechanisms
- Protein Structure and Dynamics
- Genomics and Chromatin Dynamics
- Nuclear Structure and Function
- RNA regulation and disease
- Biochemistry top 5%
- Lipid metabolism and biosynthesis
Papers in
-
- RNA Research and Splicing 4
- RNA modifications and cancer 3
- RNA and protein synthesis mechanisms 3
- PI3K/AKT/mTOR signaling in cancer 1
- Nuclear Structure and Function 1
- Genetics 2
- Genetics and Neurodevelopmental Disorders 2
- Chronic Lymphocytic Leukemia Research 1
- Co-authors
- Julie D. Forman‐Kay (5 shared papers)Robert M. Vernon (3 shared papers)Tae Hun Kim (2 shared papers)Alaji Bah (2 shared papers)P. Andrew Chong (2 shared papers)Patrick Farber (1 shared paper)Hong Lin (1 shared paper)Nahum Sonenberg (2 shared papers)
- Journals
- Cell (1 paper)American Journal of Hematology (1 paper)Proceedings of the National Academy of Sciences (1 paper)Science (1 paper)Science Advances (1 paper)
- Partner nations
- CanadaUnited StatesItaly
In The Last Decade
Brian Tsang
7 papers receiving 1.4k citations
Brian Tsang's Hit Papers
Peers
Comparison fields: 5 of 84
- Molecular Biology 1.2k
- Biochemistry 102
- Genetics 47
- Neurology 57
- Cell Biology 65
Countries citing papers authored by Brian Tsang
This map shows the geographic impact of Brian Tsang'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 Brian Tsang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian Tsang more than expected).
Fields of papers citing papers by Brian Tsang
This network shows the impact of papers produced by Brian Tsang. 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 Brian Tsang. The network helps show where Brian Tsang may publish in the future.
Co-authors
The 25 scholars most cited alongside Brian Tsang, 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 | Pi-Pi contacts are an overlooked protein feature relevant to phase separation Hit paper breakdown → | 2018 | 612 |
| 2 | 2019 | 251 | |
| 3 | 2019 | 250 | |
| 4 | 2020 | 191 | |
| 5 | 2021 | 45 | |
| 6 | 2014 | 12 | |
| 7 | 2023 | 10 | |
| 8 | 2023 | 0 |
About Brian Tsang
Brian Tsang is a scholar working on Molecular Biology, Genetics, Genetics, Neurology and Public Health, Environmental and Occupational Health, having authored 8 papers that have together received 1.4k indexed citations. Recurring topics across this work include RNA Research and Splicing (4 papers), RNA modifications and cancer (3 papers), RNA and protein synthesis mechanisms (3 papers), Genetics and Neurodevelopmental Disorders (2 papers), PI3K/AKT/mTOR signaling in cancer (1 paper), Chronic Lymphocytic Leukemia Research (1 paper), Nuclear Structure and Function (1 paper) and Amyotrophic Lateral Sclerosis Research (1 paper). The work is most often cited by research in Molecular Biology (1.2k citations), Biochemistry (102 citations), Genetics (47 citations), Neurology (57 citations) and Cell Biology (65 citations). Brian Tsang has collaborated with scholars based in Canada, United States and Italy. Frequent co-authors include Julie D. Forman‐Kay, Robert M. Vernon, Tae Hun Kim, Alaji Bah, P. Andrew Chong, Patrick Farber, Hong Lin, Nahum Sonenberg, Lewis E. Kay and Iva Pritišanac. Their work appears in journals such as Cell, American Journal of Hematology, Proceedings of the National Academy of Sciences, Science and Science Advances.
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.