Mark Ultsch
- Immunology top 1%
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- Monoclonal and Polyclonal Antibodies Research 18
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- Growth Hormone and Insulin-like Growth Factors 13
- Molecular Biology top 1%
- Glycosylation and Glycoproteins Research 11
- Metabolism, Diabetes, and Cancer 7
- Cancer Research top 2%
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- Enzyme Structure and Function 9
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- Blood Coagulation and Thrombosis Mechanisms 6
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- Computational Drug Discovery Methods 6
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- Lipoproteins and Cardiovascular Health 4
- Co-authors
- Abraham M. de VosAnthony A. KossiakoffJames A. WellsMichael G. MulkerrinCharles EigenbrotRobert F. KelleyBrian C. CunninghamKarl R. Clauser
- Partner nations
- United StatesFranceUnited Kingdom
In The Last Decade
Mark Ultsch
60 papers receiving 8.3k citations
Hit Papers
Peers
Comparison fields: 5 of 139
- Immunology 2.1k
- Radiology, Nuclear Medicine and Imaging 2.0k
- Endocrinology, Diabetes and Metabolism 1.4k
- Molecular Biology 4.9k
- Cancer Research 1.0k
Countries citing papers authored by Mark Ultsch
This map shows the geographic impact of Mark Ultsch'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 Mark Ultsch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Ultsch more than expected).
Fields of papers citing papers by Mark Ultsch
This network shows the impact of papers produced by Mark Ultsch. 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 Mark Ultsch. The network helps show where Mark Ultsch may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mark Ultsch, 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 | 2026 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2017 | 22 | |
| 4 | 2015 | 14 | |
| 5 | 2014 | 31 | |
| 6 | 2013 | 142 | |
| 7 | 2010 | 43 | |
| 8 | 2010 | 170 | |
| 9 | 2005 | 153 | |
| 10 | 2001 | 220 | |
| 11 | 2000 | 164 | |
| 12 | Crystal structure of NGF in complex with the ligand-binding domain of the TrkA receptor | 1999 | 2 |
| 13 | 1999 | 319 | |
| 14 | 1999 | 134 | |
| 15 | 1998 | 233 | |
| 16 | 1998 | 50 | |
| 17 | 1994 | 67 | |
| 18 | 1992 | 80 | |
| 19 | 1991 | 16 | |
| 20 | 1991 | 50 |
About Mark Ultsch
Mark Ultsch is a scholar working on Endocrinology, Diabetes and Metabolism, Radiology, Nuclear Medicine and Imaging and Hematology, having authored 62 papers that have together received 8.7k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (18 papers), Growth Hormone and Insulin-like Growth Factors (13 papers), Glycosylation and Glycoproteins Research (11 papers), Enzyme Structure and Function (9 papers), Metabolism, Diabetes, and Cancer (7 papers), Blood Coagulation and Thrombosis Mechanisms (6 papers), Computational Drug Discovery Methods (6 papers) and Lipoproteins and Cardiovascular Health (4 papers). The work is most often cited by research in Immunology (2.1k citations), Radiology, Nuclear Medicine and Imaging (2.0k citations) and Endocrinology, Diabetes and Metabolism (1.4k citations). Mark Ultsch has collaborated with scholars based in United States, France and United Kingdom. Frequent co-authors include Abraham M. de Vos, Anthony A. Kossiakoff, James A. Wells, Michael G. Mulkerrin, Charles Eigenbrot, Robert F. Kelley, Brian C. Cunningham, Karl R. Clauser, Christian Wiesmann and W.S. Somers. Their work appears in journals such as Journal of Molecular Biology, Biochemistry, Nature, Structure and Science.
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.