Hyonho Chun
- Molecular Biology
- Animal Science and Zoology top 5%
- Statistics and Probability top 5%
- Industrial and Manufacturing Engineering top 10%
- Artificial Intelligence
- Co-authors
- Hongyu ZhaoBing LiSeokcheon LeeSungbum JunYava Jones‐HallCindy H. NakatsuAriangela J. KozikDanyi Ma
- Topics
- Statistical Methods and Inference (5 papers)Bayesian Modeling and Causal Inference (3 papers)Metabolomics and Mass Spectrometry Studies (2 papers)
- Cited by
- Animal Science and ZoologyStatistics and ProbabilityIndustrial and Manufacturing Engineering
- Journals
- Journal of the American Statistical AssociationJournal of Agricultural and Food ChemistryMeat Science
- Partner nations
- United StatesSouth KoreaChina
In The Last Decade
Hyonho Chun
13 papers receiving 346 citations
Peers
Comparison fields: 5 of 96
- Molecular Biology 128
- Animal Science and Zoology 99
- Statistics and Probability 58
- Industrial and Manufacturing Engineering 51
- Artificial Intelligence 49
Countries citing papers authored by Hyonho Chun
This map shows the geographic impact of Hyonho Chun'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 Hyonho Chun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hyonho Chun more than expected).
Fields of papers citing papers by Hyonho Chun
This network shows the impact of papers produced by Hyonho Chun. 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 Hyonho Chun. The network helps show where Hyonho Chun may publish in the future.
Co-authorship network of co-authors of Hyonho Chun
This figure shows the co-authorship network connecting the top 25 collaborators of Hyonho Chun. A scholar is included among the top collaborators of Hyonho Chun 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 Hyonho Chun. Hyonho Chun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 24 | |
| 2 | 8 | |
| 3 | 61 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 60 | |
| 7 | 85 | |
| 8 | 4 | |
| 9 | 6 | |
| 10 | 21 | |
| 11 | 2 | |
| 12 | 20 | |
| 13 | 56 | |
| 14 | Novel Aspects Coming from the Directionality of Online Relationships: A Case Study of Twitter | 1 |
About Hyonho Chun
Hyonho Chun is a scholar working on Statistics and Probability, Animal Science and Zoology and Gastroenterology, having authored 14 papers that have together received 351 indexed citations. Recurring topics across this work include Statistical Methods and Inference (5 papers), Bayesian Modeling and Causal Inference (3 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). The work is most often cited by research in Animal Science and Zoology (99 citations), Statistics and Probability (58 citations) and Industrial and Manufacturing Engineering (51 citations). Hyonho Chun has collaborated with scholars based in United States, South Korea and China. Frequent co-authors include Hongyu Zhao, Bing Li, Seokcheon Lee, Sungbum Jun, Yava Jones‐Hall, Cindy H. Nakatsu, Ariangela J. Kozik, Danyi Ma, Bruce R. Cooper and Yuan H. Brad Kim. Their work appears in journals such as Journal of the American Statistical Association, Journal of Agricultural and Food Chemistry and Meat 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.