Chaok Seok

9.4k citations
128 papers · 6.2k indexed · 2 hit papers · h-index 38

Chaok Seok

124 papers receiving 6.2k citations

Hit Papers

GalaxyRefine: protein structure refinement driven by side...9482012202620162021250500750

Peers

Chaok Seok
Comparison fields: 5 of 157
  • Molecular Biology 4.4k
  • Computational Theory and Mathematics 863
  • Infectious Diseases 676
  • Biomaterials 409
  • Materials Chemistry 1.3k
Replace Peter M. Kasson with:
Peter M. Kasson United States
Lauren Wickstrom United States
Kevin Hauser United States
Jason Swails United States
Daniel R. Roe United States
Jing Huang China
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Chaok Seok relative to Peter M. Kasson United States Peter M. Kasson's profile →
Citations per field
00.5×1.5×
Peter M. Kasson · 1×
Citations per year

Countries citing papers authored by Chaok Seok

Since Specialization
Citations

This map shows the geographic impact of Chaok Seok'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 Chaok Seok with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chaok Seok more than expected).

Fields of papers citing papers by Chaok Seok

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chaok Seok. 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 Chaok Seok. The network helps show where Chaok Seok may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Chaok Seok, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Chaok Seok Line = papers co-authored together Chaok Seok links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20243
3 20244
4 202322
5 202240
6 202213
7 202211
8 202117
9 202054
10 20179
11 201793
12 201613
13 201537
14 201533
15 201470
16 201341
17 201358
18 201282
19 201135
20 20101

About Chaok Seok

Chaok Seok is a scholar working on Computational Theory and Mathematics, Molecular Biology, Materials Chemistry, Spectroscopy and Structural Biology, having authored 128 papers that have together received 6.2k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (59 papers), Enzyme Structure and Function (41 papers), Computational Drug Discovery Methods (22 papers), RNA and protein synthesis mechanisms (19 papers), Mass Spectrometry Techniques and Applications (14 papers), Microbial Metabolic Engineering and Bioproduction (9 papers), Receptor Mechanisms and Signaling (8 papers) and Machine Learning in Materials Science (7 papers). The work is most often cited by research in Molecular Biology (4.4k citations), Computational Theory and Mathematics (863 citations), Infectious Diseases (676 citations), Biomaterials (409 citations) and Materials Chemistry (1.3k citations). Chaok Seok has collaborated with scholars based in South Korea, United States and Puerto Rico. Frequent co-authors include Lim Heo, Hahnbeom Park, Ken A. Dill, Evangelos A. Coutsias, Jin Hwan Ko, Hasup Lee, Gyu Rie Lee, Woong‐Hee Shin, Minkyung Baek and John D. Chodera. Their work appears in journals such as Proteins Structure Function and Bioinformatics, Nucleic Acids Research, Journal of Computational Chemistry, Journal of Chemical Information and Modeling and Journal of Chemical Theory and Computation.

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.

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