George Buchlis
Impact in
- Immunology top 10%
- Immune cells in cancer
- Immunotherapy and Immune Responses
- Oncology top 10%
- CAR-T cell therapy research
- Cancer Immunotherapy and Biomarkers
Papers in
- Genetics 11
- Virus-based gene therapy research 11
-
- Viral Infectious Diseases and Gene Expression in Insects 5
- RNA Interference and Gene Delivery 2
- Co-authors
- Katherine A. High (7 shared papers)Federico Mingozzi (4 shared papers)Veena Kapoor (3 shared papers)Jing Sun (3 shared papers)Steven Μ. Albelda (3 shared papers)Guanjun Cheng (3 shared papers)Zvi G. Fridlender (2 shared papers)Liang‐Chuan S. Wang (2 shared papers)
- Journals
- Molecular Therapy (3 papers)Blood (3 papers)The Journal of Immunology (2 papers)The AAPS Journal (2 papers)Cancer Research (2 papers)
- Partner nations
- United StatesChinaIsrael
In The Last Decade
George Buchlis
15 papers receiving 851 citations
Peers
Comparison fields: 5 of 74
- Immunology 287
- Oncology 367
- Genetics 339
- Molecular Biology 459
- Hematology 50
Countries citing papers authored by George Buchlis
This map shows the geographic impact of George Buchlis'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 George Buchlis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites George Buchlis more than expected).
Fields of papers citing papers by George Buchlis
This network shows the impact of papers produced by George Buchlis. 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 George Buchlis. The network helps show where George Buchlis may publish in the future.
Co-authors
The 25 scholars most cited alongside George Buchlis, 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 | 2012 | 179 | |
| 2 | 2009 | 151 | |
| 3 | 2010 | 124 | |
| 4 | 2010 | 86 | |
| 5 | 2008 | 71 | |
| 6 | 2010 | 52 | |
| 7 | 2011 | 41 | |
| 8 | 2013 | 39 | |
| 9 | 2021 | 32 | |
| 10 | 2024 | 27 | |
| 11 | 2015 | 27 | |
| 12 | 2013 | 20 | |
| 13 | 2023 | 18 | |
| 14 | Potency Assay for AAV Vector Encoding Retinal Pigment Epithelial 65 Protein | 2016 | 1 |
| 15 | 2010 | 1 |
About George Buchlis
George Buchlis is a scholar working on Genetics, Molecular Biology, Oncology, Immunology and Cardiology and Cardiovascular Medicine, having authored 15 papers that have together received 869 indexed citations. Recurring topics across this work include Virus-based gene therapy research (11 papers), CAR-T cell therapy research (6 papers), Viral Infectious Diseases and Gene Expression in Insects (5 papers), Immunotherapy and Immune Responses (3 papers), Cancer Immunotherapy and Biomarkers (2 papers), RNA Interference and Gene Delivery (2 papers), Immune Cell Function and Interaction (2 papers) and Viral Infections and Immunology Research (2 papers). The work is most often cited by research in Immunology (287 citations), Oncology (367 citations), Genetics (339 citations), Molecular Biology (459 citations) and Hematology (50 citations). George Buchlis has collaborated with scholars based in United States, China and Israel. Frequent co-authors include Katherine A. High, Federico Mingozzi, Veena Kapoor, Jing Sun, Steven Μ. Albelda, Guanjun Cheng, Zvi G. Fridlender, Liang‐Chuan S. Wang, Linda A. Snyder and Sunil Singhal. Their work appears in journals such as Molecular Therapy, Blood, The Journal of Immunology, The AAPS Journal and Cancer Research.
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.