Stephen D. Gillies
- Immunology top 0.2%
- Immunotherapy and Immune Responses 56
- Immune Cell Function and Interaction 25
- T-cell and B-cell Immunology 15
- Oncology top 0.5%
- CAR-T cell therapy research 45
-
- Monoclonal and Polyclonal Antibodies Research 49
- Neurology top 0.5%
- Neuroblastoma Research and Treatments 38
- Molecular Biology top 1%
- Glycosylation and Glycoproteins Research 22
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- Virus-based gene therapy research 17
- Co-authors
- Susumu TonegawaSherie L. MorrisonVernon T. OiRalph A. ReisfeldKin-Ming LoPaul M. SondelHolger N. LodeRupert Handgretinger
- Partner nations
- United StatesGermanyJapan
In The Last Decade
Stephen D. Gillies
150 papers receiving 9.4k citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Immunology 4.5k
- Oncology 3.7k
- Radiology, Nuclear Medicine and Imaging 2.4k
- Neurology 1.4k
- Molecular Biology 4.0k
Countries citing papers authored by Stephen D. Gillies
This map shows the geographic impact of Stephen D. Gillies'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 Stephen D. Gillies with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen D. Gillies more than expected).
Fields of papers citing papers by Stephen D. Gillies
This network shows the impact of papers produced by Stephen D. Gillies. 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 Stephen D. Gillies. The network helps show where Stephen D. Gillies may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Stephen D. Gillies, 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 | 2020 | 12 | |
| 2 | 2019 | 53 | |
| 3 | 2018 | 54 | |
| 4 | 2017 | 41 | |
| 5 | 2016 | 119 | |
| 6 | 2012 | 21 | |
| 7 | 2011 | 77 | |
| 8 | 2008 | 47 | |
| 9 | 2007 | 31 | |
| 10 | 2005 | 28 | |
| 11 | HuBC1-IL12: A very potent immunocytokine which targets the oncofetal fibronectin in the extracellular matrix of tumor vasculature | 2004 | 1 |
| 12 | Engineering of an IL-2 immunocytokine with very low toxicity that retains potent anti-tumor activity in immune competent and immune deficient mouse tumor models | 2004 | 2 |
| 13 | 2004 | 32 | |
| 14 | 2003 | 37 | |
| 15 | 2001 | 79 | |
| 16 | MIG(CXCL9)ケモカイン遺伝子療法と抗体-サイトカイン融合蛋白質の併用はマウス結腸癌の増殖と播種を抑制する | 2001 | 1 |
| 17 | 2000 | 4 | |
| 18 | 1999 | 5 | |
| 19 | 1998 | 20 | |
| 20 | 1996 | 60 |
About Stephen D. Gillies
Stephen D. Gillies is a scholar working on Immunology, Neurology and Oncology, having authored 153 papers that have together received 9.8k indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (56 papers), Monoclonal and Polyclonal Antibodies Research (49 papers), CAR-T cell therapy research (45 papers), Neuroblastoma Research and Treatments (38 papers), Immune Cell Function and Interaction (25 papers), Glycosylation and Glycoproteins Research (22 papers), Virus-based gene therapy research (17 papers) and T-cell and B-cell Immunology (15 papers). The work is most often cited by research in Immunology (4.5k citations), Oncology (3.7k citations) and Radiology, Nuclear Medicine and Imaging (2.4k citations). Stephen D. Gillies has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include Susumu Tonegawa, Sherie L. Morrison, Vernon T. Oi, Ralph A. Reisfeld, Kin-Ming Lo, Paul M. Sondel, Holger N. Lode, Rupert Handgretinger, R. Reisfeld and Jacquelyn A. Hank. Their work appears in journals such as Nature, Cell and Proceedings of the National Academy of Sciences.
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.