Sangmi Jun

48 papers receiving 2.4k citations

Hit Papers

Rapid Detection of COVID-19 Causative Virus (SARS-CoV-2) in Human Nasopharyngeal Swab Specimens Using Field-Effect Transistor-Based Biosensor 2020 · 1.4k citations
1.4k0+2+4Years since publication4008001.2k

Peers

Sangmi Jun
Comparison fields: 5 of 131
  • Infectious Diseases 1.0k
  • Structural Biology 68
  • Biomedical Engineering 1.1k
  • Bioengineering 92
  • Biophysics 88
Replace Yun Zhu with:
Yun Zhu China
Zhifeng Shao United States
Kai Ludwig Germany
Till Böcking Australia
Zongqiang Cui China
Chris Webb United States
Matthias Amrein Canada
Katrin Schilcher United States
Bart W. Hoogenboom United Kingdom
Vicente M. Aguilella Spain
Sangmi Jun relative to Yun Zhu China Yun Zhu's profile →
Citations per field
00.5×4.0×
Yun Zhu · 1×
Citations per year

Countries citing papers authored by Sangmi Jun

Since Specialization
Citations

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

Fields of papers citing papers by Sangmi Jun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Rapid Detection of COVID-19 Causative Virus (SARS-CoV-2) in Human Nasopharyngeal Swab Specimens Using Field-Effect Transistor-Based Biosensor
Hit paper breakdown →
20201422
2 2007203
3 201178
4 201873
5 200753
6 202052
7 200949
8 201542
9 202034
10 201634
11 200634
12 201926
13 201925
14 202023
15 201920
16 202419
17 201619
18 201919
19 202118
20 201418

About Sangmi Jun

Sangmi Jun is a scholar working on Molecular Biology, Materials Chemistry, Structural Biology, Epidemiology and Physiology, having authored 49 papers that have together received 2.4k indexed citations. Recurring topics across this work include Advanced Electron Microscopy Techniques and Applications (8 papers), Alzheimer's disease research and treatments (5 papers), Supramolecular Self-Assembly in Materials (4 papers), Genomics and Phylogenetic Studies (3 papers), Gold and Silver Nanoparticles Synthesis and Applications (3 papers), Vector-borne infectious diseases (3 papers), Luminescence and Fluorescent Materials (3 papers) and Advanced Fluorescence Microscopy Techniques (3 papers). The work is most often cited by research in Infectious Diseases (1.0k citations), Structural Biology (68 citations), Biomedical Engineering (1.1k citations), Bioengineering (92 citations) and Biophysics (88 citations). Sangmi Jun has collaborated with scholars based in South Korea, United States and Ethiopia. Frequent co-authors include Seung Il Kim, Edmond Changkyun Park, Chang‐Seop Lee, Mi Jeong Kim, Bum‐Tae Kim, Keun Bon Ku, Seong‐Jun Kim, Hong Gi Kim, Daeui Park and Jeong‐O Lee. Their work appears in journals such as Scientific Reports, Advanced Functional Materials, Angewandte Chemie International Edition, Biochemistry and International Journal of Molecular Sciences.

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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