Stanimir Vuk‐Pavlović
- Immunology top 2%
- Immunotherapy and Immune Responses 20
- Immune Cell Function and Interaction 8
- T-cell and B-cell Immunology 6
- Modeling and Simulation top 2%
- Mathematical Biology Tumor Growth 6
- Oncology top 5%
- CAR-T cell therapy research 8
- Cancer Immunotherapy and Biomarkers 6
- Hematology top 5%
- Molecular Biology top 10%
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- Hemoglobin structure and function 13
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- Advanced NMR Techniques and Applications 7
- Co-authors
- Allan B. DietzPeggy A. BulurGaylord J. KnutsonŽeljko BajzerDennis A. GastineauZvia AgurFrank H. ValoneRonald L. Richardson
- Journals
- Blood (6 papers)Biochemical and Biophysical Research Communications (4 papers)The Prostate (3 papers)
- Partner nations
- United StatesCroatiaIsrael
In The Last Decade
Stanimir Vuk‐Pavlović
66 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 121
- Immunology 1.3k
- Modeling and Simulation 190
- Oncology 865
- Hematology 167
- Molecular Biology 862
Countries citing papers authored by Stanimir Vuk‐Pavlović
This map shows the geographic impact of Stanimir Vuk‐Pavlović'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 Stanimir Vuk‐Pavlović with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stanimir Vuk‐Pavlović more than expected).
Fields of papers citing papers by Stanimir Vuk‐Pavlović
This network shows the impact of papers produced by Stanimir Vuk‐Pavlović. 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 Stanimir Vuk‐Pavlović. The network helps show where Stanimir Vuk‐Pavlović may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Stanimir Vuk‐Pavlović, 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 | 2015 | 5 | |
| 2 | 2013 | 23 | |
| 3 | 2012 | 44 | |
| 4 | 2012 | 13 | |
| 5 | 2010 | 99 | |
| 6 | 2008 | 57 | |
| 7 | 2004 | 156 | |
| 8 | 2004 | 8 | |
| 9 | 2004 | 13 | |
| 10 | 2002 | 6 | |
| 11 | 2002 | 10 | |
| 12 | 2001 | 17 | |
| 13 | 2001 | 4 | |
| 14 | 2000 | 31 | |
| 15 | 1995 | 74 | |
| 16 | 1992 | 2 | |
| 17 | 1992 | 4 | |
| 18 | 1991 | 16 | |
| 19 | 1985 | 4 | |
| 20 | A Proton Magnetic Relaxation Study of tpe Interaction between Methaemoglobin and Inositol Hexaphosphate | 1974 | 9 |
About Stanimir Vuk‐Pavlović
Stanimir Vuk‐Pavlović is a scholar working on Modeling and Simulation, Immunology and Cell Biology, having authored 68 papers that have together received 2.5k indexed citations. Recurring topics across this work include Immunotherapy and Immune Responses (20 papers), Hemoglobin structure and function (13 papers), CAR-T cell therapy research (8 papers), Immune Cell Function and Interaction (8 papers), Advanced NMR Techniques and Applications (7 papers), Mathematical Biology Tumor Growth (6 papers), Cancer Immunotherapy and Biomarkers (6 papers) and T-cell and B-cell Immunology (6 papers). The work is most often cited by research in Immunology (1.3k citations), Modeling and Simulation (190 citations) and Oncology (865 citations). Stanimir Vuk‐Pavlović has collaborated with scholars based in United States, Croatia and Israel. Frequent co-authors include Allan B. Dietz, Peggy A. Bulur, Gaylord J. Knutson, Željko Bajzer, Dennis A. Gastineau, Zvia Agur, Frank H. Valone, Ronald L. Richardson, Patrick Burch and Xinghua Zhao. Their work appears in journals such as Blood, Biochemical and Biophysical Research Communications, The Prostate, Cytotherapy and Biochemistry.
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.