J.J. Haaijman
- Immunology top 2%
- Radiology, Nuclear Medicine and Imaging top 2%
- Molecular Biology
- Hematology top 5%
- Nephrology top 2%
- Topics
- Monoclonal and Polyclonal Antibodies Research (28 papers)T-cell and B-cell Immunology (19 papers)Glycosylation and Glycoproteins Research (12 papers)
- Partner nations
- NetherlandsUnited StatesNorth Macedonia
In The Last Decade
J.J. Haaijman
59 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 110
- Immunology 1.1k
- Radiology, Nuclear Medicine and Imaging 621
- Molecular Biology 475
- Hematology 283
- Nephrology 228
Countries citing papers authored by J.J. Haaijman
This map shows the geographic impact of J.J. Haaijman'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 J.J. Haaijman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J.J. Haaijman more than expected).
Fields of papers citing papers by J.J. Haaijman
This network shows the impact of papers produced by J.J. Haaijman. 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 J.J. Haaijman. The network helps show where J.J. Haaijman may publish in the future.
Co-authorship network of co-authors of J.J. Haaijman
This figure shows the co-authorship network connecting the top 25 collaborators of J.J. Haaijman. A scholar is included among the top collaborators of J.J. Haaijman 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 J.J. Haaijman. J.J. Haaijman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 4 | |
| 3 | 6 | |
| 4 | 55 | |
| 5 | Immunofluorescence: quantitative considerations. | 9 |
| 6 | 12 | |
| 7 | 5 | |
| 8 | 29 | |
| 9 | 18 | |
| 10 | 56 | |
| 11 | 168 | |
| 12 | 10 | |
| 13 | 28 | |
| 14 | 25 | |
| 15 | 25 | |
| 16 | The bone marrow: the major source of serum immunoglobulins, but still a neglected site of antibody formation. | 309 |
| 17 | Frequencies of background cytoplasmic Ig-containing cells in various lymphoid organs of athymic asplenic (lasat), athymic, asplenic and normal BALB/c mice. | 3 |
| 18 | Serum immunoglobulins in nude mice and their heterozygous littermates during ageing. | 31 |
| 19 | 18 | |
| 20 | 6 |
About J.J. Haaijman
J.J. Haaijman is a scholar working on Immunology, Radiology, Nuclear Medicine and Imaging and Virology, having authored 59 papers that have together received 2.0k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (28 papers), T-cell and B-cell Immunology (19 papers) and Glycosylation and Glycoproteins Research (12 papers). The work is most often cited by research in Immunology (1.1k citations), Nephrology (228 citations) and Radiology, Nuclear Medicine and Imaging (621 citations). J.J. Haaijman has collaborated with scholars based in Netherlands, United States and North Macedonia. Frequent co-authors include J Rádl, R. Benner, W. Hijmans, Jiří Městecký, P Brandtzæg, K Kett, Kyoko Hayakawa, Mohamed R. Daha, Thomas A. Brown and Richard R. Hardy. Their work appears in journals such as Nature, The Journal of Experimental Medicine and The Journal of 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.