Nelson D. Horseman
- Molecular Biology top 5%
- Endocrinology, Diabetes and Metabolism top 1%
- Oncology top 5%
- Genetics top 2%
- Immunology top 5%
- Co-authors
- Kenneth DorshkindLaura L. HernandezVaibhav P. PaiKaren A. GregersonLi‐Yuan Yu‐LeeArchie J. VomachkaAaron M. MarshallArthur R. Buckley
- Topics
- Growth Hormone and Insulin-like Growth Factors (26 papers)Cytokine Signaling Pathways and Interactions (14 papers)S100 Proteins and Annexins (10 papers)
- Cited by
- Endocrinology, Diabetes and MetabolismBehavioral NeuroscienceEndocrine and Autonomic Systems
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryJournal of Neuroscience
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Nelson D. Horseman
103 papers receiving 4.2k citations
Peers
Comparison fields: 5 of 120
- Molecular Biology 1.4k
- Endocrinology, Diabetes and Metabolism 1.1k
- Oncology 897
- Genetics 868
- Immunology 565
Countries citing papers authored by Nelson D. Horseman
This map shows the geographic impact of Nelson D. Horseman'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 Nelson D. Horseman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nelson D. Horseman more than expected).
Fields of papers citing papers by Nelson D. Horseman
This network shows the impact of papers produced by Nelson D. Horseman. 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 Nelson D. Horseman. The network helps show where Nelson D. Horseman may publish in the future.
Co-authorship network of co-authors of Nelson D. Horseman
This figure shows the co-authorship network connecting the top 25 collaborators of Nelson D. Horseman. A scholar is included among the top collaborators of Nelson D. Horseman 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 Nelson D. Horseman. Nelson D. Horseman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 13 | |
| 3 | 19 | |
| 4 | 77 | |
| 5 | 41 | |
| 6 | 55 | |
| 7 | 116 | |
| 8 | 14 | |
| 9 | 15 | |
| 10 | 35 | |
| 11 | 22 | |
| 12 | 10 | |
| 13 | 3 | |
| 14 | 82 | |
| 15 | 49 | |
| 16 | 11 | |
| 17 | 8 | |
| 18 | 480 | |
| 19 | 32 | |
| 20 | 9 |
About Nelson D. Horseman
Nelson D. Horseman is a scholar working on Endocrinology, Diabetes and Metabolism, Endocrine and Autonomic Systems and Behavioral Neuroscience, having authored 104 papers that have together received 4.3k indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (26 papers), Cytokine Signaling Pathways and Interactions (14 papers) and S100 Proteins and Annexins (10 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (1.1k citations), Behavioral Neuroscience (173 citations) and Endocrine and Autonomic Systems (318 citations). Nelson D. Horseman has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Kenneth Dorshkind, Laura L. Hernandez, Vaibhav P. Pai, Karen A. Gregerson, Li‐Yuan Yu‐Lee, Archie J. Vomachka, Aaron M. Marshall, Arthur R. Buckley, R.J. Collier and Jason P. Bailey. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Neuroscience.
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.