Junsu Ko

640 citations
9 papers · 233 · h-index 6

Impact in

    • Computational Drug Discovery Methods
    • Protein Structure and Dynamics
    • Bioinformatics and Genomic Networks
    • Chemical Synthesis and Analysis
    • Microbial Metabolic Engineering and Bioproduction
    • Genetics, Bioinformatics, and Biomedical Research

Papers in

Junsu Ko

9 papers receiving 229 citations

Peers

Junsu Ko
Comparison fields: 5 of 53
  • Computational Theory and Mathematics 149
  • Molecular Biology 144
  • Materials Chemistry 97
  • Pharmacology 23
  • Health Informatics 1
Replace Arkadii Lin with:
Arkadii Lin France
Kangjie Lin China
Jintu Zhang China
Benben Liao China
Lieyang Chen United States
Maurício Boff de Ávila Brazil
Odin Zhang China
Vigneshwari Subramanian United Kingdom
Alejandro Varela‐Rial Spain
Junsu Ko relative to Arkadii Lin France Arkadii Lin's profile →
Citations per field
00.5×1.5×
Arkadii Lin · 1×
Citations per year

Countries citing papers authored by Junsu Ko

Since Specialization
Citations

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

Fields of papers citing papers by Junsu Ko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1 202090
2 202263
3 201135
4 202124
5 20248
6 20246
7 20223
8 20232
9 20242

About Junsu Ko

Junsu Ko is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Pharmacology and Oncology, having authored 9 papers that have together received 233 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (5 papers), Protein Structure and Dynamics (3 papers), Microbial Natural Products and Biosynthesis (2 papers), PARP inhibition in cancer therapy (1 paper), DNA Repair Mechanisms (1 paper), Cancer Genomics and Diagnostics (1 paper), Enzyme Structure and Function (1 paper) and Luminescence and Fluorescent Materials (1 paper). The work is most often cited by research in Computational Theory and Mathematics (149 citations), Molecular Biology (144 citations), Materials Chemistry (97 citations), Pharmacology (23 citations) and Health Informatics (1 citation). Junsu Ko has collaborated with scholars based in South Korea, Japan and Ethiopia. Frequent co-authors include Juyong Lee, Woong‐Hee Shin, Yongbeom Kwon, Chaok Seok, Taek Kang, Lim Heo, Jooyoung Lee, Bomin Kim, Sanghee Lee and Yiyu Hong. Their work appears in journals such as Journal of Cheminformatics, Scientific Reports, Nature Communications, Bioorganic & Medicinal Chemistry and Journal of Computational Chemistry.

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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