Min‐Kyung So

1.7k total citations · 1 hit paper
34 papers, 1.4k citations indexed

About

Min‐Kyung So is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Materials Chemistry. According to data from OpenAlex, Min‐Kyung So has authored 34 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 5 papers in Pulmonary and Respiratory Medicine and 5 papers in Materials Chemistry. Recurrent topics in Min‐Kyung So's work include Advanced biosensing and bioanalysis techniques (7 papers), bioluminescence and chemiluminescence research (6 papers) and Biosensors and Analytical Detection (4 papers). Min‐Kyung So is often cited by papers focused on Advanced biosensing and bioanalysis techniques (7 papers), bioluminescence and chemiluminescence research (6 papers) and Biosensors and Analytical Detection (4 papers). Min‐Kyung So collaborates with scholars based in South Korea, United States and India. Min‐Kyung So's co-authors include Jianghong Rao, Sanjiv S. Gambhir, Andreas M. Loening, Chenjie Xu, Hequan Yao, Robert Sinclair, Yun Xing, Ai Leen Koh, Yan Zhang and Zuyong Xia and has published in prestigious journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and Nature Biotechnology.

In The Last Decade

Min‐Kyung So

30 papers receiving 1.4k citations

Hit Papers

Self-illuminating quantum dot conjugates for in vivo imaging 2006 2026 2012 2019 2006 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Self-illuminating quantum dot conjugates for in vivo imaging
    2006 621 citations Min‐Kyung So, Chenjie Xu et al. Nature Biotechnology profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Min‐Kyung So South Korea 12 934 560 526 109 92 34 1.4k
Hequan Yao United States 11 908 1.0× 580 1.0× 646 1.2× 217 2.0× 100 1.1× 13 1.6k
Anca Dragulescu‐Andrasi United States 16 1.1k 1.2× 346 0.6× 729 1.4× 206 1.9× 139 1.5× 17 1.8k
James A. J. Fitzpatrick United States 12 565 0.6× 325 0.6× 342 0.7× 151 1.4× 297 3.2× 17 1.1k
Samuel Clarke Canada 12 661 0.7× 636 1.1× 236 0.4× 54 0.5× 113 1.2× 29 1.1k
Kelly Boeneman United States 17 1.3k 1.4× 1.1k 2.0× 421 0.8× 86 0.8× 46 0.5× 19 1.8k
Joonhyuck Park South Korea 18 467 0.5× 729 1.3× 514 1.0× 58 0.5× 34 0.4× 32 1.4k
Chensu Wang United States 16 947 1.0× 411 0.7× 972 1.8× 82 0.8× 20 0.2× 26 2.4k
Susan Andreko United States 8 305 0.3× 282 0.5× 222 0.4× 72 0.7× 81 0.9× 9 667
Donna Coleman United States 7 762 0.8× 431 0.8× 274 0.5× 65 0.6× 58 0.6× 8 1.3k
Halina Anton France 16 348 0.4× 297 0.5× 328 0.6× 91 0.8× 68 0.7× 27 877

Countries citing papers authored by Min‐Kyung So

Since Specialization
Citations

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

Fields of papers citing papers by Min‐Kyung So

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Min‐Kyung So. 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 Min‐Kyung So. The network helps show where Min‐Kyung So may publish in the future.

Co-authorship network of co-authors of Min‐Kyung So

This figure shows the co-authorship network connecting the top 25 collaborators of Min‐Kyung So. A scholar is included among the top collaborators of Min‐Kyung So 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 Min‐Kyung So. Min‐Kyung So is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Park, Kyung, Sunghwan Shin, Jong-Ho Park, et al.. (2025). Applying National Whole-genome Sequencing Findings for Rare Diseases in Clinical Practice: The Imperative of a Multidisciplinary Approach. Annals of Laboratory Medicine. 46(1). 94–103.
2.
So, Min‐Kyung, et al.. (2025). The Novel HLA‐C*07:1193 Allele Was Identified by Next‐Generation Sequencing. HLA. 106(5). e70482–e70482.
3.
Chung, Hae‐Sun, et al.. (2025). Evaluating the Use of Generative Artificial Intelligence to Support Genetic Counseling for Rare Diseases. Diagnostics. 15(6). 672–672. 4 indexed citations
4.
So, Min‐Kyung, et al.. (2025). The Novel HLA‐DRB1*12:113 Allele Was Identified by Next‐Generation Sequencing. HLA. 106(1). e70339–e70339. 1 indexed citations
5.
So, Min‐Kyung, et al.. (2025). Characterization of Penicillin-Non-Susceptible, Multidrug-Resistant Streptococcus agalactiae Using Whole-Genome Sequencing. Current Microbiology. 82(8). 344–344. 1 indexed citations
6.
7.
8.
Huh, Jungwon, et al.. (2023). P393: Effectiveness of group genetic counseling session via metaverse. SHILAP Revista de lepidopterología. 1(1). 100429–100429. 1 indexed citations
9.
10.
Moon, Hye Sung, Min‐Kyung So, Tae‐Dong Jeong, et al.. (2023). Evaluation of Group Genetic Counseling Sessions via a Metaverse-based Application. Annals of Laboratory Medicine. 44(1). 82–91. 3 indexed citations
11.
So, Min‐Kyung, Hyun Kyu Ahn, Jungwon Huh, & Kwang Hyun Kim. (2022). Germline pathogenic variants in unselected Korean men with prostate cancer. Investigative and Clinical Urology. 63(3). 294–294. 3 indexed citations
12.
13.
Woo, Se Joon, Baek‐Lok Oh, Jinu Han, et al.. (2021). Genetic Characteristics and Phenotype of Korean Patients with Stickler Syndrome: A Korean Multicenter Analysis Report No. 1. Genes. 12(10). 1578–1578. 5 indexed citations
14.
So, Min‐Kyung, et al.. (2021). Variant Prediction by Analyzing RdRp/S Gene Double or Low Amplification Pattern in Allplex SARS-CoV-2 Assay. Diagnostics. 11(10). 1854–1854. 11 indexed citations
15.
Hua, Serenus, Mary Saunders, Lauren M. Dimapasoc, et al.. (2013). Differentiation of Cancer Cell Origin and Molecular Subtype by Plasma Membrane N-Glycan Profiling. Journal of Proteome Research. 13(2). 961–968. 40 indexed citations
16.
So, Min‐Kyung, Hequan Yao, & Jianghong Rao. (2008). HaloTag protein-mediated specific labeling of living cells with quantum dots. Biochemical and Biophysical Research Communications. 374(3). 419–423. 58 indexed citations
17.
So, Min‐Kyung, Gayatri Gowrishankar, Sumitaka Hasegawa, June‐Key Chung, & Jianghong Rao. (2008). Imaging Target mRNA and siRNA‐Mediated Gene Silencing In Vivo with Ribozyme‐Based Reporters. ChemBioChem. 9(16). 2682–2691. 14 indexed citations
18.
Yao, Hequan, Min‐Kyung So, & Jianghong Rao. (2007). A Bioluminogenic Substrate for In Vivo Imaging of β‐Lactamase Activity. Angewandte Chemie International Edition. 46(37). 7031–7034. 109 indexed citations
19.
So, Min‐Kyung, Chenjie Xu, Andreas M. Loening, Sanjiv S. Gambhir, & Jianghong Rao. (2006). Self-illuminating quantum dot conjugates for in vivo imaging. Nature Biotechnology. 24(3). 339–343. 621 indexed citations breakdown →
20.
So, Min‐Kyung, Andreas M. Loening, Sanjiv S. Gambhir, & Jianghong Rao. (2006). Creating self-illuminating quantum dot conjugates. Nature Protocols. 1(3). 1160–1164. 93 indexed citations

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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