L. Kirszbaum
Impact in
- Oncology top 5%
- Clusterin in disease pathology
- Immunology top 10%
- Biomarkers in Disease Mechanisms
- Complement system in diseases
Papers in
-
- Glycosylation and Glycoproteins Research 7
- Machine Learning in Bioinformatics 2
-
- Complement system in diseases 4
- T-cell and B-cell Immunology 3
- Co-authors
- Ian D. Walker (14 shared papers)A. J. F. D'Apice (3 shared papers)Brendan F. Murphy (3 shared papers)Peter J. Hudson (2 shared papers)Brendan J. Classon (3 shared papers)B. Murphy (2 shared papers)Jocelyn R. Saunders (2 shared papers)Moira K. O’Bryan (2 shared papers)
- Journals
- Biochemical and Biophysical Research Communications (2 papers)Journal of Clinical Investigation (2 papers)Proceedings of the National Academy of Sciences (2 papers)Immunogenetics (2 papers)Gene (1 paper)
- Partner nations
- AustraliaSouth KoreaFinland
In The Last Decade
L. Kirszbaum
18 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 83
- Oncology 593
- Immunology 332
- Periodontics 39
- Physiology 170
- Reproductive Medicine 50
Countries citing papers authored by L. Kirszbaum
This map shows the geographic impact of L. Kirszbaum'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 L. Kirszbaum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites L. Kirszbaum more than expected).
Fields of papers citing papers by L. Kirszbaum
This network shows the impact of papers produced by L. Kirszbaum. 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 L. Kirszbaum. The network helps show where L. Kirszbaum may publish in the future.
Co-authors
The 25 scholars most cited alongside L. Kirszbaum, 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 | 1988 | 280 | |
| 2 | 1989 | 214 | |
| 3 | 1990 | 110 | |
| 4 | 1989 | 101 | |
| 5 | 1986 | 69 | |
| 6 | 1992 | 59 | |
| 7 | 1995 | 44 | |
| 8 | 1993 | 34 | |
| 9 | 1986 | 32 | |
| 10 | 1989 | 19 | |
| 11 | 1987 | 19 | |
| 12 | 1986 | 16 | |
| 13 | 1986 | 12 | |
| 14 | 1995 | 10 | |
| 15 | 1991 | 10 | |
| 16 | 2008 | 5 | |
| 17 | 1994 | 2 | |
| 18 | Molecular analysis of Ly-2/3 and L3T4 molecules. | 1986 | 1 |
About L. Kirszbaum
L. Kirszbaum is a scholar working on Molecular Biology, Immunology, Oncology, Radiology, Nuclear Medicine and Imaging and Hematology, having authored 18 papers that have together received 1.0k indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (7 papers), Clusterin in disease pathology (4 papers), Complement system in diseases (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), T-cell and B-cell Immunology (3 papers), Erythrocyte Function and Pathophysiology (3 papers), Iron Metabolism and Disorders (2 papers) and Machine Learning in Bioinformatics (2 papers). The work is most often cited by research in Oncology (593 citations), Immunology (332 citations), Periodontics (39 citations), Physiology (170 citations) and Reproductive Medicine (50 citations). L. Kirszbaum has collaborated with scholars based in Australia, South Korea and Finland. Frequent co-authors include Ian D. Walker, A. J. F. D'Apice, Brendan F. Murphy, Peter J. Hudson, Brendan J. Classon, B. Murphy, Jocelyn R. Saunders, Moira K. O’Bryan, Ian F. C. McKenzie and Anthony J.F. d’Apice. Their work appears in journals such as Biochemical and Biophysical Research Communications, Journal of Clinical Investigation, Proceedings of the National Academy of Sciences, Immunogenetics and Gene.
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.