Daniel K. Hsu
Impact in
- Immunology top 0.1%
- Galectins and Cancer Biology
- Toxin Mechanisms and Immunotoxins
- Macrophage Migration Inhibitory Factor
- Molecular Biology top 1%
- Signaling Pathways in Disease
- Glycosylation and Glycoproteins Research
- Protein Tyrosine Phosphatases
Papers in
- Immunology 85
- Galectins and Cancer Biology 78
- Toxin Mechanisms and Immunotoxins 18
- Macrophage Migration Inhibitory Factor 10
- T-cell and Retrovirus Studies 5
- Immune Cell Function and Interaction 5
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- Signaling Pathways in Disease 27
- Glycosylation and Glycoproteins Research 18
Daniel K. Hsu
100 papers receiving 8.7k citations
Hit Papers
Peers
Comparison fields: 5 of 140
- Immunology 6.5k
- Molecular Biology 4.7k
- Oncology 1.2k
- Physiology 1.1k
- Immunology and Allergy 164
Countries citing papers authored by Daniel K. Hsu
This map shows the geographic impact of Daniel K. Hsu'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 Daniel K. Hsu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel K. Hsu more than expected).
Fields of papers citing papers by Daniel K. Hsu
This network shows the impact of papers produced by Daniel K. Hsu. 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 Daniel K. Hsu. The network helps show where Daniel K. Hsu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniel K. Hsu, 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 | 2025 | 4 | |
| 2 | 2023 | 9 | |
| 3 | 2020 | 31 | |
| 4 | 2020 | 3 | |
| 5 | 2014 | 23 | |
| 6 | 2012 | 95 | |
| 7 | 2011 | 19 | |
| 8 | Galectin-3 negatively regulates TCR-mediated CD4+T cell activation at the immunological synapse | 2009 | 14 |
| 9 | 2009 | 1 | |
| 10 | 2009 | 132 | |
| 11 | 2008 | 139 | |
| 12 | 2008 | 88 | |
| 13 | 2008 | 44 | |
| 14 | 2007 | 1 | |
| 15 | 2006 | 177 | |
| 16 | 2006 | 424 | |
| 17 | 2006 | 86 | |
| 18 | 2004 | 71 | |
| 19 | 2000 | 423 | |
| 20 | 1999 | 168 |
About Daniel K. Hsu
Daniel K. Hsu is a scholar working on Immunology, Molecular Biology, Oncology, Parasitology and Clinical Biochemistry, having authored 101 papers that have together received 8.9k indexed citations. Recurring topics across this work include Galectins and Cancer Biology (78 papers), Signaling Pathways in Disease (27 papers), Glycosylation and Glycoproteins Research (18 papers), Toxin Mechanisms and Immunotoxins (18 papers), Peptidase Inhibition and Analysis (13 papers), Macrophage Migration Inhibitory Factor (10 papers), T-cell and Retrovirus Studies (5 papers) and Immune Cell Function and Interaction (5 papers). The work is most often cited by research in Immunology (6.5k citations), Molecular Biology (4.7k citations), Oncology (1.2k citations), Physiology (1.1k citations) and Immunology and Allergy (164 citations). Daniel K. Hsu has collaborated with scholars based in United States, Taiwan and Brazil. Frequent co-authors include Fu‐Tong Liu, Ri‐Yao Yang, Lan Yu, Ichiro Kuwabara, F T Liu, Riaz I. Zuberi, John Apgar, Hideki Sano, Linda G. Baum and Huan‐Yuan Chen. Their work appears in journals such as The Journal of Immunology, Journal of Investigative Dermatology, American Journal Of Pathology, Journal of Biological Chemistry and Biochemical and Biophysical Research Communications.
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.