Jee-Hyub Kim

799 citations
21 papers · 374 indexed · h-index 11

Impact in

Papers in

Jee-Hyub Kim

21 papers receiving 361 citations

Peers

Jee-Hyub Kim
Comparison fields: 5 of 81
  • Plant Science 160
  • Information Systems and Management 27
  • Molecular Biology 189
  • Artificial Intelligence 68
  • Statistics, Probability and Uncertainty 14
Replace Shuiqing Huang with:
Shuiqing Huang China
Leslie Derr United States
Jan Taubert United Kingdom
Yuko Tsumoto Japan
Joe Stubbs United States
Boris Capitanu United States
Nic Herndon United States
Fabio Simeoni United Kingdom
Damian D. G. Gessler United States
Alain Malpertuy France
Jee-Hyub Kim relative to Shuiqing Huang China Shuiqing Huang's profile →
Citations per field
00.5×2.8×
Shuiqing Huang · 1×
Citations per year

Countries citing papers authored by Jee-Hyub Kim

Since Specialization
Citations

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

Fields of papers citing papers by Jee-Hyub Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jee-Hyub Kim. 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 Jee-Hyub Kim. The network helps show where Jee-Hyub Kim may publish in the future.

Co-authors

The 25 scholars most cited alongside Jee-Hyub Kim, 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 Jee-Hyub Kim Line = papers co-authored together Jee-Hyub Kim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202115
2 201725
3 201535
4 201323
5 20133
6 201311
7 20138
8 201311
9
Finding small molecule and protein pairs in scientific literature using a bootstrapping method
20121
10 201217
11 200710
12 200514
13 2004154
14 200311
15 20036
16 20026
17 20014
18 20004
19
The use of FAB mass spectrometry and pyroglutamate aminopeptidase digestion for the structure determination of pyroglutamate in modified peptides.
19952
20 19917

About Jee-Hyub Kim

Jee-Hyub Kim is a scholar working on Public Administration, Information Systems and Management, Otorhinolaryngology, Artificial Intelligence and Molecular Biology, having authored 21 papers that have together received 374 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (9 papers), Natural Language Processing Techniques (5 papers), Topic Modeling (3 papers), Bioinformatics and Genomic Networks (3 papers), Text and Document Classification Technologies (3 papers), Machine Learning in Bioinformatics (2 papers), Web Data Mining and Analysis (2 papers) and Scientific Computing and Data Management (2 papers). The work is most often cited by research in Plant Science (160 citations), Information Systems and Management (27 citations), Molecular Biology (189 citations), Artificial Intelligence (68 citations) and Statistics, Probability and Uncertainty (14 citations). Jee-Hyub Kim has collaborated with scholars based in United Kingdom, South Korea and Switzerland. Frequent co-authors include So Young Yi, Seung Hun Yu, Young-Hee Joung, Sanghyeob Lee, Doil Choi, Johanna McEntyre, Şenay Kafkas, Xingjun Pi, Dietrich Rebholz‐Schuhmann and Alex Mitchell. Their work appears in journals such as Journal of Biomedical Semantics, Bioinformatics, PLoS ONE, PLANT PHYSIOLOGY and Journal of Dental 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026