Hojung Nam
- Molecular Biology top 5%
- Computational Theory and Mathematics top 0.5%
- Biomedical Engineering top 10%
- Materials Chemistry top 10%
- Genetics top 10%
- Co-authors
- Ingoo LeeBernhard Ø. PalssonJoshua A. LermanTom M ConradAdam M. FeistJeffrey D. OrthDoheon LeeEunyoung Kim
- Topics
- Computational Drug Discovery Methods (22 papers)Bioinformatics and Genomic Networks (16 papers)Protein Structure and Dynamics (8 papers)
- Journals
- NatureScienceNucleic Acids Research
- Partner nations
- South KoreaUnited StatesAustria
In The Last Decade
Hojung Nam
59 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 152
- Molecular Biology 2.2k
- Computational Theory and Mathematics 827
- Biomedical Engineering 420
- Materials Chemistry 378
- Genetics 293
Countries citing papers authored by Hojung Nam
This map shows the geographic impact of Hojung 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 Hojung Nam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hojung Nam more than expected).
Fields of papers citing papers by Hojung Nam
This network shows the impact of papers produced by Hojung 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 Hojung Nam. The network helps show where Hojung Nam may publish in the future.
Co-authorship network of co-authors of Hojung Nam
This figure shows the co-authorship network connecting the top 25 collaborators of Hojung Nam. A scholar is included among the top collaborators of Hojung Nam 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 Hojung Nam. Hojung Nam 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 | 0 | |
| 3 | 0 | |
| 4 | 24 | |
| 5 | 72 | |
| 6 | 33 | |
| 7 | DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequencesbreakdown → | 414 |
| 8 | The CH25H–CYP7B1–RORα axis of cholesterol metabolism regulates osteoarthritisbreakdown → | 235 |
| 9 | 12 | |
| 10 | 14 | |
| 11 | 31 | |
| 12 | 20 | |
| 13 | 10 | |
| 14 | 55 | |
| 15 | 6 | |
| 16 | A comprehensive genome‐scale reconstruction of Escherichia coli metabolism—2011breakdown → | 767 |
| 17 | 23 | |
| 18 | 10 | |
| 19 | 14 | |
| 20 | Nanoscale observation of domain configuration and switching of ferroelectric nanolayers | 2 |
About Hojung Nam
Hojung Nam is a scholar working on Computational Theory and Mathematics, Molecular Biology and Microbiology, having authored 66 papers that have together received 2.9k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (22 papers), Bioinformatics and Genomic Networks (16 papers) and Protein Structure and Dynamics (8 papers). The work is most often cited by research in Computational Theory and Mathematics (827 citations), Molecular Biology (2.2k citations) and Cancer Research (235 citations). Hojung Nam has collaborated with scholars based in South Korea, United States and Austria. Frequent co-authors include Ingoo Lee, Bernhard Ø. Palsson, Joshua A. Lerman, Tom M Conrad, Adam M. Feist, Jeffrey D. Orth, Doheon Lee, Eunyoung Kim, Nathan E. Lewis and Dae‐Hee Lee. Their work appears in journals such as Nature, Science and Nucleic Acids Research.
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.