Hyun S. Nahm
- Molecular Biology
- Pulmonary and Respiratory Medicine top 10%
- Genetics
- Endocrinology, Diabetes and Metabolism top 10%
- Reproductive Medicine top 5%
- Co-authors
- Darrell N. WardNorman M. GreenbergMilton J. FinegoldJeffrey R. GingrichMichael W. KattanR BarriosWan-Kyng LiuWilliam M. Lamkin
- Topics
- Animal Nutrition and Physiology (3 papers)Growth Hormone and Insulin-like Growth Factors (3 papers)Lipid Membrane Structure and Behavior (3 papers)
- Cited by
- Reproductive MedicineEndocrinology, Diabetes and MetabolismPulmonary and Respiratory Medicine
- Partner nations
- United StatesAustralia
In The Last Decade
Hyun S. Nahm
15 papers receiving 722 citations
Peers
Comparison fields: 5 of 65
- Molecular Biology 387
- Pulmonary and Respiratory Medicine 259
- Genetics 169
- Endocrinology, Diabetes and Metabolism 161
- Reproductive Medicine 123
Countries citing papers authored by Hyun S. Nahm
This map shows the geographic impact of Hyun S. Nahm'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 Hyun S. Nahm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hyun S. Nahm more than expected).
Fields of papers citing papers by Hyun S. Nahm
This network shows the impact of papers produced by Hyun S. Nahm. 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 Hyun S. Nahm. The network helps show where Hyun S. Nahm may publish in the future.
Co-authorship network of co-authors of Hyun S. Nahm
This figure shows the co-authorship network connecting the top 25 collaborators of Hyun S. Nahm. A scholar is included among the top collaborators of Hyun S. Nahm 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 Hyun S. Nahm. Hyun S. Nahm is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 94 | |
| 2 | 29 | |
| 3 | Androgen-independent prostate cancer progression in the TRAMP model. | 281 |
| 4 | 29 | |
| 5 | 30 | |
| 6 | 6 | |
| 7 | 7 | |
| 8 | 6 | |
| 9 | 7 | |
| 10 | 64 | |
| 11 | 82 | |
| 12 | 93 | |
| 13 | The amino acid sequence of the S-aminoethylated ovine luteinizing hormone s-subunit (LH- ). | 3 |
| 14 | 26 | |
| 15 | [Different effects of thyroxin homologs on the blood cholesterol content and on oxygen consumption]. | 3 |
About Hyun S. Nahm
Hyun S. Nahm is a scholar working on Animal Science and Zoology, Endocrinology, Diabetes and Metabolism and Reproductive Medicine, having authored 15 papers that have together received 760 indexed citations. Recurring topics across this work include Animal Nutrition and Physiology (3 papers), Growth Hormone and Insulin-like Growth Factors (3 papers) and Lipid Membrane Structure and Behavior (3 papers). The work is most often cited by research in Reproductive Medicine (123 citations), Endocrinology, Diabetes and Metabolism (161 citations) and Pulmonary and Respiratory Medicine (259 citations). Hyun S. Nahm has collaborated with scholars based in United States and Australia. Frequent co-authors include Darrell N. Ward, Norman M. Greenberg, Milton J. Finegold, Jeffrey R. Gingrich, Michael W. Kattan, R Barrios, Wan-Kyng Liu, William M. Lamkin, H. Nordean Baker and S. Glenn. Their work appears in journals such as Journal of Biological Chemistry, Biochemistry and Endocrinology.
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.