Daniel Sze
Impact in
- Immunology top 1%
- T-cell and B-cell Immunology
- Immune Cell Function and Interaction
- Immunotherapy and Immune Responses
- Hematology top 2%
- Multiple Myeloma Research and Treatments
Papers in
-
- Metabolomics and Mass Spectrometry Studies 4
- Immunology 24
- T-cell and B-cell Immunology 17
- Immunotherapy and Immune Responses 14
- Immune Cell Function and Interaction 10
- Co-authors
- Gcf Chan (6 shared papers)Wing Keung Chan (4 shared papers)Kai‐Michael Toellner (8 shared papers)Ian C. M. MacLennan (5 shared papers)Carola G. Vinuesa (3 shared papers)Dale R. Taylor (3 shared papers)Ross Brown (13 shared papers)Aaron C. Tan (7 shared papers)
In The Last Decade
Daniel Sze
73 papers receiving 4.4k citations
Daniel Sze's Hit Papers
Peers
Comparison fields: 5 of 152
- Immunology 2.0k
- Hematology 496
- Pharmacology 488
- Complementary and alternative medicine 236
- Biochemistry 155
Countries citing papers authored by Daniel Sze
This map shows the geographic impact of Daniel Sze'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 Sze with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Sze more than expected).
Fields of papers citing papers by Daniel Sze
This network shows the impact of papers produced by Daniel Sze. 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 Sze. The network helps show where Daniel Sze may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Sze, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 75 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | The effects of β-glucan on human immune and cancer cells Hit paper breakdown → | 2009 | 728 |
| 2 | 2003 | 488 | |
| 3 | 2001 | 292 | |
| 4 | 2000 | 248 | |
| 5 | 1997 | 241 | |
| 6 | 2013 | 225 | |
| 7 | 1998 | 194 | |
| 8 | 2012 | 187 | |
| 9 | 1996 | 165 | |
| 10 | 2002 | 150 | |
| 11 | 2011 | 123 | |
| 12 | 2016 | 121 | |
| 13 | 2001 | 110 | |
| 14 | 2013 | 72 | |
| 15 | 2012 | 70 | |
| 16 | 2008 | 58 | |
| 17 | 2000 | 55 | |
| 18 | 2021 | 53 | |
| 19 | 2018 | 53 | |
| 20 | 2004 | 52 |
About Daniel Sze
Daniel Sze is a scholar working on Molecular Biology, Immunology, Hematology, Complementary and alternative medicine and Oncology, having authored 75 papers that have together received 4.5k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (17 papers), Immunotherapy and Immune Responses (14 papers), Multiple Myeloma Research and Treatments (10 papers), Immune Cell Function and Interaction (10 papers), Monoclonal and Polyclonal Antibodies Research (5 papers), Traditional Chinese Medicine Studies (5 papers), Phytochemicals and Antioxidant Activities (5 papers) and Metabolomics and Mass Spectrometry Studies (4 papers). The work is most often cited by research in Immunology (2.0k citations), Hematology (496 citations), Pharmacology (488 citations), Complementary and alternative medicine (236 citations) and Biochemistry (155 citations). Daniel Sze has collaborated with scholars based in Australia, Hong Kong and China. Frequent co-authors include Gcf Chan, Wing Keung Chan, Kai‐Michael Toellner, Ian C. M. MacLennan, Carola G. Vinuesa, Dale R. Taylor, Ross Brown, Aaron C. Tan, Ka‐Wai Cheung and John Gibson. Their work appears in journals such as Blood, The Journal of Experimental Medicine, Nutrition and Cancer, Evidence-based Complementary and Alternative Medicine and British Journal of Haematology.
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.