Hyun‐Jun Nam
Impact in
Papers in
-
- Protein Structure and Dynamics 5
- RNA and protein synthesis mechanisms 4
- Machine Learning in Bioinformatics 2
- Genomics and Phylogenetic Studies 1
- Genetics 3
- Genetic Associations and Epidemiology 2
- Genomics and Rare Diseases 2
- Co-authors
- Guan Ning Lin (3 shared papers)Lilia M. Iakoucheva (3 shared papers)Kymberleigh A. Pagel (2 shared papers)Predrag Radivojac (2 shared papers)D.N. Cooper (2 shared papers)Vikas Pejaver (2 shared papers)Jonathan Sebat (2 shared papers)Sean D. Mooney (2 shared papers)
- Journals
- Scientific Reports (1 paper)BMB Reports (1 paper)Cell Death and Disease (1 paper)Nature Communications (1 paper)ACS Photonics (1 paper)
- Partner nations
- South KoreaUnited StatesUnited Kingdom
In The Last Decade
Hyun‐Jun Nam
14 papers receiving 759 citations
Hyun‐Jun Nam's Hit Papers
Peers
Comparison fields: 5 of 100
- Aging 97
- Genetics 223
- Molecular Biology 501
- Endocrine and Autonomic Systems 30
- Clinical Biochemistry 26
Countries citing papers authored by Hyun‐Jun Nam
This map shows the geographic impact of Hyun‐Jun Nam'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‐Jun Nam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hyun‐Jun Nam more than expected).
Fields of papers citing papers by Hyun‐Jun Nam
This network shows the impact of papers produced by Hyun‐Jun Nam. 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‐Jun Nam. The network helps show where Hyun‐Jun Nam may publish in the future.
Co-authors
The 25 scholars most cited alongside Hyun‐Jun Nam, 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 | Inferring the molecular and phenotypic impact of amino acid variants with MutPred2 Hit paper breakdown → | 2020 | 426 |
| 2 | 2014 | 155 | |
| 3 | 2017 | 49 | |
| 4 | 2011 | 39 | |
| 5 | 2013 | 28 | |
| 6 | 2009 | 18 | |
| 7 | 2015 | 10 | |
| 8 | 2019 | 10 | |
| 9 | 2013 | 8 | |
| 10 | 2022 | 7 | |
| 11 | 2012 | 6 | |
| 12 | 2013 | 3 | |
| 13 | 2017 | 3 | |
| 14 | 2025 | 1 | |
| 15 | 2024 | 0 |
About Hyun‐Jun Nam
Hyun‐Jun Nam is a scholar working on Molecular Biology, Genetics, Cell Biology, Aging and Endocrine and Autonomic Systems, having authored 15 papers that have together received 763 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (5 papers), RNA and protein synthesis mechanisms (4 papers), Machine Learning in Bioinformatics (2 papers), Genetics, Aging, and Longevity in Model Organisms (2 papers), Genetic Associations and Epidemiology (2 papers), Genomics and Rare Diseases (2 papers), Nonlinear Optical Materials Studies (1 paper) and Genomics and Phylogenetic Studies (1 paper). The work is most often cited by research in Aging (97 citations), Genetics (223 citations), Molecular Biology (501 citations), Endocrine and Autonomic Systems (30 citations) and Clinical Biochemistry (26 citations). Hyun‐Jun Nam has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Guan Ning Lin, Lilia M. Iakoucheva, Kymberleigh A. Pagel, Predrag Radivojac, D.N. Cooper, Vikas Pejaver, Jonathan Sebat, Sean D. Mooney, Matthew Mort and Jorge Urresti. Their work appears in journals such as Scientific Reports, BMB Reports, Cell Death and Disease, Nature Communications and ACS Photonics.
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.