Roza Nurieva
- Immunology top 0.05%
- Oncology top 0.5%
- Molecular Biology top 5%
- Pathology and Forensic Medicine top 0.5%
- Physiology top 2%
- Co-authors
- Chen DongXuexian O. YangQiang TianSeon Hee ChangYeonseok ChungStephanie S. WatowichYi-Hong WangGustavo Martínez
- Topics
- T-cell and B-cell Immunology (50 papers)Immune Cell Function and Interaction (44 papers)Immunotherapy and Immune Responses (20 papers)
- Cited by
- ImmunologyOncologyDermatology
- Partner nations
- United StatesChinaRussia
In The Last Decade
Roza Nurieva
75 papers receiving 17.3k citations
Hit Papers
Peers
Comparison fields: 5 of 122
- Immunology 14.3k
- Oncology 3.1k
- Molecular Biology 2.4k
- Pathology and Forensic Medicine 1.4k
- Physiology 1.2k
Countries citing papers authored by Roza Nurieva
This map shows the geographic impact of Roza Nurieva'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 Roza Nurieva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roza Nurieva more than expected).
Fields of papers citing papers by Roza Nurieva
This network shows the impact of papers produced by Roza Nurieva. 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 Roza Nurieva. The network helps show where Roza Nurieva may publish in the future.
Co-authorship network of co-authors of Roza Nurieva
This figure shows the co-authorship network connecting the top 25 collaborators of Roza Nurieva. A scholar is included among the top collaborators of Roza Nurieva 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 Roza Nurieva. Roza Nurieva is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 49 | |
| 2 | 54 | |
| 3 | STAT4 Regulates the CD8+ Regulatory T Cell/T Follicular Helper Cell Axis and Promotes Atherogenesis in Insulin-Resistant Ldlr-/- Mice | 0 |
| 4 | 25 | |
| 5 | 4 | |
| 6 | 42 | |
| 7 | 260 | |
| 8 | 187 | |
| 9 | 102 | |
| 10 | 25 | |
| 11 | 84 | |
| 12 | 71 | |
| 13 | 3 | |
| 14 | 65 | |
| 15 | Regulation of inflammatory responses by IL-17Fbreakdown → | 625 |
| 16 | T Helper 17 Lineage Differentiation Is Programmed by Orphan Nuclear Receptors RORα and RORγbreakdown → | 1310 |
| 17 | Generation of T Follicular Helper Cells Is Mediated by Interleukin-21 but Independent of T Helper 1, 2, or 17 Cell Lineagesbreakdown → | 957 |
| 18 | STAT3 Regulates Cytokine-mediated Generation of Inflammatory Helper T Cellsbreakdown → | 1202 |
| 19 | 37 | |
| 20 | 189 |
About Roza Nurieva
Roza Nurieva is a scholar working on Immunology, Oncology and Hematology, having authored 76 papers that have together received 17.5k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (50 papers), Immune Cell Function and Interaction (44 papers) and Immunotherapy and Immune Responses (20 papers). The work is most often cited by research in Immunology (14.3k citations), Oncology (3.1k citations) and Dermatology (928 citations). Roza Nurieva has collaborated with scholars based in United States, China and Russia. Frequent co-authors include Chen Dong, Xuexian O. Yang, Qiang Tian, Seon Hee Chang, Yeonseok Chung, Stephanie S. Watowich, Yi-Hong Wang, Gustavo Martínez, Anton M. Jetten and Athanasia D. Panopoulos. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.
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.