David T. Curiel
- Genetics top 0.01%
- Virus-based gene therapy research 454
- Oncology top 0.05%
- CAR-T cell therapy research 226
- Biotechnology top 0.02%
- Cancer Research and Treatments 76
- Molecular Biology top 0.1%
- Viral Infectious Diseases and Gene Expression in Insects 176
- RNA Interference and Gene Delivery 162
- CRISPR and Genetic Engineering 53
- Immunology top 0.5%
- Immunotherapy and Immune Responses 59
-
- Viral gastroenteritis research and epidemiology 48
- Co-authors
- Victor KrasnykhIgor P. DmitrievRamón AlemanyJoanne T. DouglasGalina MikheevaRonald D. AlvarezGene P. SiegalMinghui Wang
- Cited by
- GeneticsOncologyBiotechnology
- Journals
- Proceedings of the National Academy of Sciences (6 papers)Nucleic Acids Research (1 paper)Journal of Biological Chemistry (5 papers)
- Partner nations
- United StatesFranceNetherlands
In The Last Decade
David T. Curiel
589 papers receiving 27.9k citations
Hit Papers
Peers
Comparison fields: 5 of 146
- Genetics 17.4k
- Oncology 11.0k
- Biotechnology 3.2k
- Molecular Biology 17.8k
- Immunology 4.3k
Countries citing papers authored by David T. Curiel
This map shows the geographic impact of David T. Curiel'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 David T. Curiel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David T. Curiel more than expected).
Fields of papers citing papers by David T. Curiel
This network shows the impact of papers produced by David T. Curiel. 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 David T. Curiel. The network helps show where David T. Curiel may publish in the future.
Co-authorship network
The 25 scholars most cited alongside David T. Curiel, 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 | 2024 | 3 | |
| 2 | 2022 | 7 | |
| 3 | 2020 | 52 | |
| 4 | COX2/mPGES1/PGE 2 pathway regulates PD-L1 expression in tumor-associated macrophages and myeloid-derived suppressor cellsbreakdown → | 2017 | 374 |
| 5 | 2016 | 17 | |
| 6 | 2015 | 9 | |
| 7 | 2012 | 49 | |
| 8 | 2011 | 26 | |
| 9 | 2011 | 101 | |
| 10 | 2010 | 102 | |
| 11 | 2010 | 89 | |
| 12 | 2010 | 65 | |
| 13 | 2009 | 22 | |
| 14 | 2009 | 40 | |
| 15 | 2008 | 101 | |
| 16 | 2008 | 41 | |
| 17 | 2006 | 33 | |
| 18 | 2004 | 46 | |
| 19 | 2002 | 11 | |
| 20 | 2002 | 1 |
About David T. Curiel
David T. Curiel is a scholar working on Genetics, Oncology and Biotechnology, having authored 595 papers that have together received 28.6k indexed citations. Recurring topics across this work include Virus-based gene therapy research (454 papers), CAR-T cell therapy research (226 papers), Viral Infectious Diseases and Gene Expression in Insects (176 papers), RNA Interference and Gene Delivery (162 papers), Cancer Research and Treatments (76 papers), Immunotherapy and Immune Responses (59 papers), CRISPR and Genetic Engineering (53 papers) and Viral gastroenteritis research and epidemiology (48 papers). The work is most often cited by research in Genetics (17.4k citations), Oncology (11.0k citations) and Biotechnology (3.2k citations). David T. Curiel has collaborated with scholars based in United States, France and Netherlands. Frequent co-authors include Victor Krasnykh, Igor P. Dmitriev, Ramón Alemany, Joanne T. Douglas, Galina Mikheeva, Ronald D. Alvarez, Gene P. Siegal, Minghui Wang, Elena A. Kashentseva and Masato Yamamoto. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.
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.