Iva Zlatareva

2.0k total citations
8 papers, 483 citations indexed

About

Iva Zlatareva is a scholar working on Immunology, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Iva Zlatareva has authored 8 papers receiving a total of 483 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Immunology, 5 papers in Oncology and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Iva Zlatareva's work include Immune Cell Function and Interaction (6 papers), T-cell and B-cell Immunology (5 papers) and CAR-T cell therapy research (3 papers). Iva Zlatareva is often cited by papers focused on Immune Cell Function and Interaction (6 papers), T-cell and B-cell Immunology (5 papers) and CAR-T cell therapy research (3 papers). Iva Zlatareva collaborates with scholars based in United Kingdom, France and Italy. Iva Zlatareva's co-authors include Adrian Hayday, Pierre Vantourout, Daisy Melandri, Andrew W. Jones, Martin J. Woodward, Ambrosius P. Snijders, Michael H. Malim, Adam Laing, Luis Apolonia and Peter M. Irving and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Immunity.

In The Last Decade

Iva Zlatareva

8 papers receiving 481 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Iva Zlatareva United Kingdom	7	402	152	63	34	19	8	483
Gabriel R. Starbeck-Miller United States	9	374 0.9×	154 1.0×	67 1.1×	26 0.8×	31 1.6×	9	431
Yasemin Virk France	3	290 0.7×	236 1.6×	118 1.9×	15 0.4×	22 1.2×	3	427
Woo‐Sung Chang South Korea	5	378 0.9×	206 1.4×	34 0.5×	10 0.3×	19 1.0×	11	421
Daisy Melandri United Kingdom	4	309 0.8×	91 0.6×	36 0.6×	14 0.4×	14 0.7×	4	350
Andrea Tazbirkova Australia	8	398 1.0×	258 1.7×	41 0.7×	19 0.6×	50 2.6×	18	487
Nela Klein-González Germany	7	243 0.6×	209 1.4×	110 1.7×	15 0.4×	16 0.8×	13	344
Louis Szeponik Sweden	9	291 0.7×	108 0.7×	67 1.1×	9 0.3×	25 1.3×	15	364
Pengfei Zhou China	8	175 0.4×	101 0.7×	130 2.1×	22 0.6×	24 1.3×	18	361
Natalie J. Neubert Switzerland	5	151 0.4×	114 0.8×	56 0.9×	15 0.4×	15 0.8×	6	224
Alfie T. Baker United Kingdom	8	214 0.5×	118 0.8×	63 1.0×	18 0.5×	12 0.6×	10	302

Countries citing papers authored by Iva Zlatareva

Since Specialization

Citations

This map shows the geographic impact of Iva Zlatareva'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 Iva Zlatareva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Iva Zlatareva more than expected).

Fields of papers citing papers by Iva Zlatareva

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Iva Zlatareva. 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 Iva Zlatareva. The network helps show where Iva Zlatareva may publish in the future.

Co-authorship network of co-authors of Iva Zlatareva

This figure shows the co-authorship network connecting the top 25 collaborators of Iva Zlatareva. A scholar is included among the top collaborators of Iva Zlatareva 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 Iva Zlatareva. Iva Zlatareva is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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8 of 8 papers shown

Davies, Daniel, Shraddha Kamdar, Richard Woolf, et al.. (2024). PD-1 defines a distinct, functional, tissue-adapted state in Vδ1+ T cells with implications for cancer immunotherapy. Nature Cancer. 5(3). 420–432. 25 indexed citations

Pinto, Madalena, Stephen M. Brown, Katsuyoshi Washio, et al.. (2024). 172 (PB160): Affimer® Drug Conjugates (AffDC) targeting Fibroblast Activation Protein-α deliver highly toxic warheads to the tumor microenvironment by leveraging the preCISION™ release mechanism. European Journal of Cancer. 211. 114693–114693. 1 indexed citations

Zlatareva, Iva & Yin Wu. (2023). Local γδ T cells: translating promise to practice in cancer immunotherapy. British Journal of Cancer. 129(3). 393–405. 12 indexed citations

Dart, Robin, Iva Zlatareva, Pierre Vantourout, et al.. (2023). Conserved γδ T cell selection by BTNL proteins limits progression of human inflammatory bowel disease. Science. 381(6663). eadh0301–eadh0301. 30 indexed citations

Hoffmann, Ricarda M., Silvia Mele, Anthony Cheung, et al.. (2020). Rapid conjugation of antibodies to toxins to select candidates for the development of anticancer Antibody-Drug Conjugates (ADCs). Scientific Reports. 10(1). 8869–8869. 15 indexed citations

Willcox, Carrie R., Pierre Vantourout, Mahboob Salim, et al.. (2019). Butyrophilin-like 3 Directly Binds a Human Vγ4+ T Cell Receptor Using a Modality Distinct from Clonally-Restricted Antigen. Immunity. 51(5). 813–825.e4. 113 indexed citations

Vantourout, Pierre, Adam Laing, Martin J. Woodward, et al.. (2018). Heteromeric interactions regulate butyrophilin (BTN) and BTN-like molecules governing γδ T cell biology. Proceedings of the National Academy of Sciences. 115(5). 1039–1044. 120 indexed citations

Melandri, Daisy, Iva Zlatareva, Raphaël A. G. Chaleil, et al.. (2018). The γδTCR combines innate immunity with adaptive immunity by utilizing spatially distinct regions for agonist selection and antigen responsiveness. Nature Immunology. 19(12). 1352–1365. 167 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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