Julia Davydova
Impact in
- Genetics top 5%
- Virus-based gene therapy research
- Biotechnology top 5%
- Cancer Research and Treatments
Papers in
- Co-authors
- Masato Yamamoto (40 shared papers)Selwyn M. Vickers (13 shared papers)David T. Curiel (10 shared papers)Victor Krasnykh (4 shared papers)Minghui Wang (2 shared papers)Eric J. Brown (5 shared papers)Gene P. Siegal (1 shared paper)Christopher J. LaRocca (10 shared papers)
- Journals
- Blood (5 papers)Viruses (5 papers)Surgery (4 papers)Journal of Cellular Biochemistry (3 papers)Oncotarget (3 papers)
- Partner nations
- United StatesRussiaJapan
In The Last Decade
Julia Davydova
59 papers receiving 945 citations
Peers
Comparison fields: 5 of 66
- Genetics 617
- Biotechnology 188
- Oncology 435
- Molecular Biology 439
- Immunology 97
Countries citing papers authored by Julia Davydova
This map shows the geographic impact of Julia Davydova'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 Julia Davydova with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julia Davydova more than expected).
Fields of papers citing papers by Julia Davydova
This network shows the impact of papers produced by Julia Davydova. 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 Julia Davydova. The network helps show where Julia Davydova may publish in the future.
Co-authors
The 25 scholars most cited alongside Julia Davydova, 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 63 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2003 | 105 | |
| 2 | 2004 | 69 | |
| 3 | 2004 | 49 | |
| 4 | 2015 | 43 | |
| 5 | 2017 | 35 | |
| 6 | 2010 | 32 | |
| 7 | 2021 | 32 | |
| 8 | 2018 | 30 | |
| 9 | 2008 | 28 | |
| 10 | 2012 | 28 | |
| 11 | 2009 | 25 | |
| 12 | 2012 | 25 | |
| 13 | 2008 | 24 | |
| 14 | 2009 | 23 | |
| 15 | 2003 | 23 | |
| 16 | 2015 | 22 | |
| 17 | 2012 | 22 | |
| 18 | 2002 | 22 | |
| 19 | 2019 | 21 | |
| 20 | 2012 | 20 |
About Julia Davydova
Julia Davydova is a scholar working on Genetics, Oncology, Molecular Biology, Biotechnology and Hematology, having authored 63 papers that have together received 955 indexed citations. Recurring topics across this work include Virus-based gene therapy research (37 papers), CAR-T cell therapy research (16 papers), Cancer Research and Treatments (13 papers), Viral Infectious Diseases and Gene Expression in Insects (7 papers), Immunotherapy and Immune Responses (7 papers), Hematopoietic Stem Cell Transplantation (5 papers), RNA Interference and Gene Delivery (5 papers) and Immune Response and Inflammation (5 papers). The work is most often cited by research in Genetics (617 citations), Biotechnology (188 citations), Oncology (435 citations), Molecular Biology (439 citations) and Immunology (97 citations). Julia Davydova has collaborated with scholars based in United States, Russia and Japan. Frequent co-authors include Masato Yamamoto, Selwyn M. Vickers, David T. Curiel, Victor Krasnykh, Minghui Wang, Eric J. Brown, Gene P. Siegal, Christopher J. LaRocca, Yoshiaki Miura and Long P. Le. Their work appears in journals such as Blood, Viruses, Surgery, Journal of Cellular Biochemistry and Oncotarget.
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.