Ivan Tatarov
Impact in
- Endocrinology top 10%
- Escherichia coli research studies
- Biophysics top 10%
- Electromagnetic Fields and Biological Effects
Papers in
- Co-authors
- Aruna Panda (5 shared papers)Angela R. Melton‐Celsa (3 shared papers)Louis J. DeTolla (4 shared papers)Alison D. O’Brien (3 shared papers)David Ayares (11 shared papers)Mark A. Smith (2 shared papers)Tonia Zangari (2 shared papers)Tianshu Zhang (10 shared papers)
- Journals
- Transplantation (5 papers)The Journal of Heart and Lung Transplantation (3 papers)Infection and Immunity (2 papers)Transplant International (1 paper)Frontiers in Immunology (1 paper)
- Partner nations
- United StatesEgypt
In The Last Decade
Ivan Tatarov
17 papers receiving 221 citations
Peers
Comparison fields: 5 of 62
- Endocrinology 66
- Biophysics 32
- Biotechnology 23
- Infectious Diseases 45
- Transplantation 6
Countries citing papers authored by Ivan Tatarov
This map shows the geographic impact of Ivan Tatarov'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 Ivan Tatarov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Tatarov more than expected).
Fields of papers citing papers by Ivan Tatarov
This network shows the impact of papers produced by Ivan Tatarov. 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 Ivan Tatarov. The network helps show where Ivan Tatarov may publish in the future.
Co-authors
The 25 scholars most cited alongside Ivan Tatarov, 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 | Effect of magnetic fields on tumor growth and viability. | 2011 | 60 |
| 2 | 2013 | 37 | |
| 3 | Escherichia coli O157:H7 infection in Dutch belted and New Zealand white rabbits. | 2010 | 20 |
| 4 | 2021 | 19 | |
| 5 | 2022 | 18 | |
| 6 | 2014 | 17 | |
| 7 | 2020 | 15 | |
| 8 | 2023 | 9 | |
| 9 | 2014 | 8 | |
| 10 | 2019 | 7 | |
| 11 | 2020 | 4 | |
| 12 | 2018 | 3 | |
| 13 | Clinical Trypanosoma cruzi Disease after Cardiac Transplantation in a Cynomolgus Macaque (Macaca fascicularis). | 2016 | 3 |
| 14 | 2020 | 3 | |
| 15 | 2016 | 2 | |
| 16 | 2016 | 1 | |
| 17 | 2023 | 1 | |
| 18 | 2017 | 0 | |
| 19 | 2023 | 0 |
About Ivan Tatarov
Ivan Tatarov is a scholar working on Surgery, Genetics, Infectious Diseases, Endocrinology and Epidemiology, having authored 19 papers that have together received 227 indexed citations. Recurring topics across this work include Xenotransplantation and immune response (9 papers), Viral gastroenteritis research and epidemiology (4 papers), Escherichia coli research studies (4 papers), Transplantation: Methods and Outcomes (4 papers), Virus-based gene therapy research (4 papers), Organ Transplantation Techniques and Outcomes (3 papers), Animal Genetics and Reproduction (2 papers) and Tissue Engineering and Regenerative Medicine (2 papers). The work is most often cited by research in Endocrinology (66 citations), Biophysics (32 citations), Biotechnology (23 citations), Infectious Diseases (45 citations) and Transplantation (6 citations). Ivan Tatarov has collaborated with scholars based in United States and Egypt. Frequent co-authors include Aruna Panda, Angela R. Melton‐Celsa, Louis J. DeTolla, Alison D. O’Brien, David Ayares, Mark A. Smith, Tonia Zangari, Tianshu Zhang, Avneesh K. Singh and Michael M. Lipsky. Their work appears in journals such as Transplantation, The Journal of Heart and Lung Transplantation, Infection and Immunity, Transplant International and Frontiers in Immunology.
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.