Sang‐Mok Choo
- Molecular Biology
- Computational Theory and Mathematics top 5%
- Materials Chemistry
- Numerical Analysis top 5%
- Computational Mechanics top 10%
- Co-authors
- S.K. ChungKwang‐Hyun ChoSung‐Young ShinWalter KölchOliver RathFrances FeeArmin ZebischBrian W. McFerran
- Topics
- Differential Equations and Numerical Methods (15 papers)Gene Regulatory Network Analysis (11 papers)Advanced Numerical Methods in Computational Mathematics (9 papers)
- Partner nations
- South KoreaPuerto RicoIreland
In The Last Decade
Sang‐Mok Choo
38 papers receiving 777 citations
Peers
Comparison fields: 5 of 112
- Molecular Biology 389
- Computational Theory and Mathematics 142
- Materials Chemistry 138
- Numerical Analysis 122
- Computational Mechanics 114
Countries citing papers authored by Sang‐Mok Choo
This map shows the geographic impact of Sang‐Mok Choo'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 Sang‐Mok Choo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sang‐Mok Choo more than expected).
Fields of papers citing papers by Sang‐Mok Choo
This network shows the impact of papers produced by Sang‐Mok Choo. 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 Sang‐Mok Choo. The network helps show where Sang‐Mok Choo may publish in the future.
Co-authorship network of co-authors of Sang‐Mok Choo
This figure shows the co-authorship network connecting the top 25 collaborators of Sang‐Mok Choo. A scholar is included among the top collaborators of Sang‐Mok Choo 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 Sang‐Mok Choo. Sang‐Mok Choo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 10 | |
| 3 | 13 | |
| 4 | 11 | |
| 5 | 121 | |
| 6 | OPTIMIZATION OF PARAMETERS IN MATHEMATICAL MODELS OF BIOLOGICAL SYSTEMS | 0 |
| 7 | FINITE DIFFERENCE SCHEMES FOR CALCIUM DIFFUSION EQUATIONS | 0 |
| 8 | 13 | |
| 9 | 13 | |
| 10 | 25 | |
| 11 | 31 | |
| 12 | 7 | |
| 13 | 18 | |
| 14 | 3 | |
| 15 | 2 | |
| 16 | 10 | |
| 17 | Cahn‐Hilliad方程式に関する保存型非線形差分スキーム‐II | 29 |
| 18 | 41 | |
| 19 | PSEUDOSPECTRAL METHOD FOR THE DAMPED BOUSSINESQ EQUATION | 7 |
| 20 | 8 |
About Sang‐Mok Choo
Sang‐Mok Choo is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Computational Mechanics, having authored 40 papers that have together received 797 indexed citations. Recurring topics across this work include Differential Equations and Numerical Methods (15 papers), Gene Regulatory Network Analysis (11 papers) and Advanced Numerical Methods in Computational Mathematics (9 papers). The work is most often cited by research in Numerical Analysis (122 citations), Modeling and Simulation (79 citations) and Computational Theory and Mathematics (142 citations). Sang‐Mok Choo has collaborated with scholars based in South Korea, Puerto Rico and Ireland. Frequent co-authors include S.K. Chung, Kwang‐Hyun Cho, Sung‐Young Shin, Walter Kölch, Oliver Rath, Frances Fee, Armin Zebisch, Brian W. McFerran, Jeong‐Rae Kim and Junil Kim. Their work appears in journals such as Cancer Research, Scientific Reports and Journal of Cell 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.