Julia Davydova

1.4k total citations
66 papers, 1.2k citations indexed

About

Julia Davydova is a scholar working on Genetics, Oncology and Biotechnology. According to data from OpenAlex, Julia Davydova has authored 66 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Genetics, 34 papers in Oncology and 25 papers in Biotechnology. Recurrent topics in Julia Davydova's work include Virus-based gene therapy research (43 papers), Cancer Research and Treatments (25 papers) and CAR-T cell therapy research (23 papers). Julia Davydova is often cited by papers focused on Virus-based gene therapy research (43 papers), Cancer Research and Treatments (25 papers) and CAR-T cell therapy research (23 papers). Julia Davydova collaborates with scholars based in United States, Russia and Japan. Julia Davydova's co-authors include Masato Yamamoto, David T. Curiel, Selwyn M. Vickers, Long P. Le, Victor Krasnykh, Minghui Wang, Igor P. Dmitriev, Maaike Everts, Eric J. Brown and Gene P. Siegal and has published in prestigious journals such as Blood, The Journal of Immunology and Gastroenterology.

In The Last Decade

Julia Davydova

63 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Julia Davydova United States 22 833 663 596 291 117 66 1.2k
Kilian Guse Finland 22 781 0.9× 717 1.1× 570 1.0× 226 0.8× 127 1.1× 32 1.3k
Ronald G. Crystal United States 7 561 0.7× 576 0.9× 234 0.4× 79 0.3× 115 1.0× 9 846
Mena Mansour United States 11 565 0.7× 354 0.5× 684 1.1× 110 0.4× 349 3.0× 23 1.2k
Carlos Alberto Fajardo Spain 13 475 0.6× 395 0.6× 720 1.2× 95 0.3× 335 2.9× 16 980
John Lam United States 13 808 1.0× 634 1.0× 582 1.0× 159 0.5× 62 0.5× 24 949
Maureen Ward United States 16 676 0.8× 793 1.2× 404 0.7× 54 0.2× 126 1.1× 39 1.1k
R L Martuza United States 12 704 0.8× 436 0.7× 377 0.6× 104 0.4× 163 1.4× 13 916
Cheryl A. Carlson United States 16 325 0.4× 376 0.6× 291 0.5× 54 0.2× 72 0.6× 23 710
Dong‐Soo Im South Korea 16 540 0.6× 845 1.3× 232 0.4× 61 0.2× 73 0.6× 30 1.3k
Soonpin Yei United States 12 814 1.0× 669 1.0× 220 0.4× 56 0.2× 150 1.3× 15 1.1k

Countries citing papers authored by Julia Davydova

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Julia Davydova

This figure shows the co-authorship network connecting the top 25 collaborators of Julia Davydova. A scholar is included among the top collaborators of Julia Davydova based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Julia Davydova. Julia Davydova is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
LaRocca, Christopher J., et al.. (2023). Viral Shedding in Mice following Intravenous Adenovirus Injection: Impact on Biosafety Classification. Viruses. 15(7). 1495–1495. 1 indexed citations
2.
Гражданцева, А. А., et al.. (2023). Development of Oncolytic Vectors Based on Human Adenovirus Type 6 for Cancer Treatment. Viruses. 15(1). 182–182. 5 indexed citations
3.
LaRocca, Christopher J., et al.. (2023). 428 Development of an Oncolytic Adenovirus to Treat Metastatic Colorectal Cancer. Journal of Clinical and Translational Science. 7(s1). 128–128. 1 indexed citations
4.
Davydova, Julia, et al.. (2023). Infectivity-Enhanced, Conditionally Replicative Adenovirus for COX-2-Expressing Castration-Resistant Prostate Cancer. Viruses. 15(4). 901–901. 5 indexed citations
5.
Iguchi, Eriko, Stanislav O. Zakharkin, Christopher J. LaRocca, et al.. (2021). Cancer imaging and therapy utilizing a novel NIS-expressing adenovirus: The role of adenovirus death protein deletion. Molecular Therapy — Oncolytics. 20. 659–668. 10 indexed citations
7.
Паровичникова, Е. Н., et al.. (2017). Absolute Lymphocyte Count after First Induction Is Associated with Relapse Free Survival in Acute Myeloid Leukemia. Blood. 130. 5087–5087. 1 indexed citations
8.
Davydova, Julia, et al.. (2017). Impact of post-transplant cyclophosphamide after hematopoietic stem cell transplantation on chimerism in T-regulatory cells. 6. 1 indexed citations
10.
LaRocca, Christopher J., Amanda Ribeiro de Oliveira, Ryan Shanley, et al.. (2015). Oncolytic adenovirus expressing interferon alpha in a syngeneic Syrian hamster model for the treatment of pancreatic cancer. Surgery. 157(5). 888–898. 43 indexed citations
11.
Fukuyama, Yoshiko, Daisuke Tokuhara, Shinichi Sekine, et al.. (2013). Potential Roles of CCR5+ CCR6+ Dendritic Cells Induced by Nasal Ovalbumin plus Flt3 Ligand Expressing Adenovirus for Mucosal IgA Responses. PLoS ONE. 8(4). e60453–e60453. 8 indexed citations
12.
Arrington, Amanda K., et al.. (2012). Generation of a novel, cyclooxygenase-2–targeted, interferon-expressing, conditionally replicative adenovirus for pancreatic cancer therapy. The American Journal of Surgery. 204(5). 741–750. 28 indexed citations
13.
Davydova, Julia, et al.. (2012). Delivery of interferon alpha using a novel Cox2-controlled adenovirus for pancreatic cancer therapy. Surgery. 152(1). 114–122. 22 indexed citations
14.
Fukuyama, Yoshiko, Daisuke Tokuhara, Shinichi Sekine, et al.. (2011). Notch-ligand expression by NALT dendritic cells regulates mucosal Th1- and Th2-type responses. Biochemical and Biophysical Research Communications. 418(1). 6–11. 12 indexed citations
15.
Davydova, Julia, Eric J. Brown, Xianghua Luo, et al.. (2009). In vivo bioimaging tracks conditionally replicative adenoviral replication and provides an early indication of viral antitumor efficacy. Cancer Science. 101(2). 474–481. 25 indexed citations
16.
17.
Nelson, Amy R., Julia Davydova, David T. Curiel, & Masato Yamamoto. (2009). Combination of conditionally replicative adenovirus and standard chemotherapies shows synergistic antitumor effect in pancreatic cancer. Cancer Science. 100(11). 2181–2187. 16 indexed citations
18.
Vickers, Selwyn M., Hidetaka Ono, Julia Davydova, et al.. (2008). Optimization of conditionally replicative adenovirus for pancreatic cancer and its evaluation in an orthotopic murine xenograft model. The American Journal of Surgery. 195(4). 481–490. 24 indexed citations
19.
Sekine, Shinichi, Kosuke Kataoka, Hideki Asanuma, et al.. (2007). NALT CD11b+ Dendritic Cell Migration Contributes to Induction of Ag Specific Immunity (B111). The Journal of Immunology. 178(1_Supplement). LB23–LB23. 2 indexed citations
20.
Yamamoto, Masato, Julia Davydova, Minghui Wang, et al.. (2003). Infectivity enhanced, cyclooxygenase-2 promoter-based conditionally replicative adenovirus for pancreatic cancer. Gastroenterology. 125(4). 1203–1218. 105 indexed citations

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.

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