Jong Cheol Jeong
- Molecular Biology top 5%
- Machine Learning in Bioinformatics 4
- Bioinformatics and Genomic Networks 4
- Gene expression and cancer classification 4
- Protein Structure and Dynamics 3
- Genomics and Phylogenetic Studies 3
- Biomedical Text Mining and Ontologies 2
- Microbiology top 5%
- Cell Biology top 10%
-
- Topic Modeling 3
-
- Data Quality and Management 3
- Co-authors
- Yifei QiWonpil ImJeffery B. KlaudaSunhwan JoMin Sun YeomJason SwailsAlexander D. MacKerellJoshua Buckner
- Partner nations
- United StatesSouth KoreaIndia
In The Last Decade
Jong Cheol Jeong
18 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 146
- Molecular Biology 2.4k
- Computational Theory and Mathematics 372
- Microbiology 116
- Cellular and Molecular Neuroscience 299
- Cell Biology 188
Countries citing papers authored by Jong Cheol Jeong
This map shows the geographic impact of Jong Cheol Jeong'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 Jong Cheol Jeong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jong Cheol Jeong more than expected).
Fields of papers citing papers by Jong Cheol Jeong
This network shows the impact of papers produced by Jong Cheol Jeong. 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 Jong Cheol Jeong. The network helps show where Jong Cheol Jeong may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jong Cheol Jeong, 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 | 2024 | 5 | |
| 2 | 2023 | 2 | |
| 3 | 2023 | 1 | |
| 4 | 2022 | 0 | |
| 5 | 2022 | 1 | |
| 6 | 2021 | 3 | |
| 7 | 2020 | 31 | |
| 8 | 2019 | 15 | |
| 9 | 2018 | 54 | |
| 10 | 2016 | 1 | |
| 11 | 2015 | 37 | |
| 12 | CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Fieldbreakdown → | 2015 | 2803 |
| 13 | 2014 | 13 | |
| 14 | 2014 | 1 | |
| 15 | 2014 | 6 | |
| 16 | 2013 | 5 | |
| 17 | 2010 | 156 | |
| 18 | 2009 | 117 | |
| 19 | 2007 | 22 |
About Jong Cheol Jeong
Jong Cheol Jeong is a scholar working on Transplantation, Information Systems and Management and Management Science and Operations Research, having authored 19 papers that have together received 3.3k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (4 papers), Bioinformatics and Genomic Networks (4 papers), Gene expression and cancer classification (4 papers), Protein Structure and Dynamics (3 papers), Topic Modeling (3 papers), Genomics and Phylogenetic Studies (3 papers), Data Quality and Management (3 papers) and Biomedical Text Mining and Ontologies (2 papers). The work is most often cited by research in Molecular Biology (2.4k citations), Computational Theory and Mathematics (372 citations) and Microbiology (116 citations). Jong Cheol Jeong has collaborated with scholars based in United States, South Korea and India. Frequent co-authors include Yifei Qi, Wonpil Im, Jeffery B. Klauda, Sunhwan Jo, Min Sun Yeom, Jason Swails, Alexander D. MacKerell, Joshua Buckner, Vijay S. Pande and Shuai Wei. Their work appears in journals such as Bioinformatics, Clinical Cancer Research and Biophysical Journal.
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.