Dejun Tang
Impact in
-
- Multiple Sclerosis Research Studies
- Ophthalmology top 10%
- Ocular Diseases and Behçet’s Syndrome
Papers in
-
- Sphingolipid Metabolism and Signaling 3
- Glycosylation and Glycoproteins Research 1
-
- Biosimilars and Bioanalytical Methods 3
- Galectins and Cancer Biology 1
- Co-authors
- William Collins (3 shared papers)Ludwig Kappos (2 shared papers)Anthony T. Reder (2 shared papers)Lixin Zhang-Auberson (2 shared papers)Xiaoli Zhang (1 shared paper)Lee M. Jampol (1 shared paper)Marco A. Zarbin (1 shared paper)Paul O’Connor (1 shared paper)
- Journals
- Multiple Sclerosis Journal (2 papers)Clinical Radiology (1 paper)Neurology (1 paper)Statistics in Biopharmaceutical Research (1 paper)Ophthalmology (1 paper)
- Partner nations
- ChinaUnited StatesSwitzerland
In The Last Decade
Dejun Tang
17 papers receiving 467 citations
Peers
Comparison fields: 5 of 69
- Pathology and Forensic Medicine 203
- Ophthalmology 40
- Statistics and Probability 37
- Neurology 51
- Psychiatry and Mental health 45
Countries citing papers authored by Dejun Tang
This map shows the geographic impact of Dejun Tang'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 Dejun Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dejun Tang more than expected).
Fields of papers citing papers by Dejun Tang
This network shows the impact of papers produced by Dejun Tang. 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 Dejun Tang. The network helps show where Dejun Tang may publish in the future.
Co-authors
The 25 scholars most cited alongside Dejun Tang, 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 | 2013 | 121 | |
| 2 | 2013 | 108 | |
| 3 | 2014 | 69 | |
| 4 | 2012 | 66 | |
| 5 | 2005 | 57 | |
| 6 | 2005 | 35 | |
| 7 | 2018 | 4 | |
| 8 | 2019 | 3 | |
| 9 | Choice of priors for hierarchical models: Admissibility and computation | 2001 | 3 |
| 10 | 2007 | 3 | |
| 11 | 2024 | 2 | |
| 12 | 2022 | 2 | |
| 13 | 2019 | 2 | |
| 14 | 2024 | 1 | |
| 15 | 2021 | 1 | |
| 16 | 2010 | 1 | |
| 17 | 2008 | 1 | |
| 18 | 2012 | 1 | |
| 19 | 2012 | 0 | |
| 20 | 2018 | 0 |
About Dejun Tang
Dejun Tang is a scholar working on Molecular Biology, Immunology, Control and Systems Engineering, Statistics and Probability and Economics and Econometrics, having authored 20 papers that have together received 480 indexed citations. Recurring topics across this work include Sphingolipid Metabolism and Signaling (3 papers), Biosimilars and Bioanalytical Methods (3 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers), Advanced Algorithms and Applications (2 papers), Statistical Methods in Clinical Trials (2 papers), Glycosylation and Glycoproteins Research (1 paper), Ferroptosis and cancer prognosis (1 paper) and Galectins and Cancer Biology (1 paper). The work is most often cited by research in Pathology and Forensic Medicine (203 citations), Ophthalmology (40 citations), Statistics and Probability (37 citations), Neurology (51 citations) and Psychiatry and Mental health (45 citations). Dejun Tang has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include William Collins, Ludwig Kappos, Anthony T. Reder, Lixin Zhang-Auberson, Xiaoli Zhang, Lee M. Jampol, Marco A. Zarbin, Paul O’Connor, Rama D. Jager and JA Cohen. Their work appears in journals such as Multiple Sclerosis Journal, Clinical Radiology, Neurology, Statistics in Biopharmaceutical Research and Ophthalmology.
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.