Kyoungmi Kim

4.7k total citations · 2 hit papers
77 papers, 3.2k citations indexed

About

Kyoungmi Kim is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, Kyoungmi Kim has authored 77 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Molecular Biology, 15 papers in Genetics and 6 papers in Oncology. Recurrent topics in Kyoungmi Kim's work include CRISPR and Genetic Engineering (22 papers), RNA regulation and disease (10 papers) and RNA and protein synthesis mechanisms (6 papers). Kyoungmi Kim is often cited by papers focused on CRISPR and Genetic Engineering (22 papers), RNA regulation and disease (10 papers) and RNA and protein synthesis mechanisms (6 papers). Kyoungmi Kim collaborates with scholars based in South Korea, United States and Japan. Kyoungmi Kim's co-authors include Jin‐Soo Kim, Daesik Kim, Sang‐Tae Kim, Kayeong Lim, Taeyoung Koo, Hyunji Lee, Robert H. Weiss, Gayoung Baek, Eugene Chung and Jeong Hun Kim and has published in prestigious journals such as Cell, Journal of Clinical Investigation and Nature Communications.

In The Last Decade

Kyoungmi Kim

70 papers receiving 3.2k citations

Hit Papers

In vivo genome editing with a small Cas9 orthologue deriv... 2017 2026 2020 2023 2017 2018 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kyoungmi Kim South Korea 26 2.7k 725 229 219 204 77 3.2k
Philippe Rouet France 24 2.3k 0.8× 560 0.8× 226 1.0× 198 0.9× 187 0.9× 56 3.0k
Li Xu China 28 1.5k 0.6× 315 0.4× 145 0.6× 307 1.4× 109 0.5× 87 2.3k
Alfred L. Fisher United States 26 2.0k 0.7× 283 0.4× 192 0.8× 160 0.7× 187 0.9× 60 3.0k
John W. Phillips United States 30 2.1k 0.8× 405 0.6× 232 1.0× 162 0.7× 324 1.6× 81 3.3k
Wenjun Zhou China 28 1.4k 0.5× 202 0.3× 75 0.3× 313 1.4× 406 2.0× 81 2.2k
Chang Seok Lee South Korea 25 1.2k 0.5× 136 0.2× 87 0.4× 222 1.0× 182 0.9× 61 2.1k
Marialuisa Lavitrano Italy 32 2.3k 0.8× 1.6k 2.2× 133 0.6× 125 0.6× 269 1.3× 136 3.5k
Changqing Li China 24 897 0.3× 161 0.2× 132 0.6× 118 0.5× 109 0.5× 72 1.4k
Jason Yu United Kingdom 15 1.1k 0.4× 138 0.2× 63 0.3× 157 0.7× 198 1.0× 21 1.8k

Countries citing papers authored by Kyoungmi Kim

Since Specialization
Citations

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

Fields of papers citing papers by Kyoungmi Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kyoungmi Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Kyoungmi Kim. A scholar is included among the top collaborators of Kyoungmi Kim 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 Kyoungmi Kim. Kyoungmi Kim 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.
Lee, Jeung‐Hee, Jiyun Yang, Ho‐Jin Lee, et al.. (2025). Robust genome editing activity and the applications of enhanced miniature CRISPR-Cas12f1. Nature Communications. 16(1). 677–677. 4 indexed citations
2.
Yang, Jiyun, Sung Han Ok, Hyunji Lee, et al.. (2025). An innovative approach using CRISPR-ribonucleoprotein packaged in virus-like particles to generate genetically engineered mouse models. Nature Communications. 16(1). 3451–3451.
3.
Choi, Seung‐Cheol, Jae Hyoung Park, Kyoungmi Kim, et al.. (2024). FGF4 and ascorbic acid enhance the maturation of induced cardiomyocytes by activating JAK2–STAT3 signaling. Experimental & Molecular Medicine. 56(10). 2231–2245. 3 indexed citations
4.
Kim, Kyoungmi, et al.. (2024). Factors affecting the cleavage efficiency of the CRISPR-Cas9 system. Animal Cells and Systems. 28(1). 75–83. 11 indexed citations
5.
Choi, Woong, et al.. (2024). Navigating the CRISPR/Cas Landscape for Enhanced Diagnosis and Treatment of Wilson’s Disease. Cells. 13(14). 1214–1214. 5 indexed citations
6.
Kim, Kyoungmi, et al.. (2023). Clinical Approaches for Mitochondrial Diseases. Cells. 12(20). 2494–2494. 9 indexed citations
7.
Lee, Hyunji, et al.. (2023). Recent Research Trends in Stem Cells Using CRISPR/Cas-Based Genome Editing Methods. International Journal of Stem Cells. 17(1). 1–14. 3 indexed citations
8.
Choi, Seung‐Cheol, Jae Hyoung Park, Ju Hyeon Kim, et al.. (2023). The Activation of the LIMK/Cofilin Signaling Pathway via Extracellular Matrix–Integrin Interactions Is Critical for the Generation of Mature and Vascularized Cardiac Organoids. Cells. 12(16). 2029–2029. 8 indexed citations
9.
Kim, Kyoungmi, et al.. (2023). Progress in and Prospects of Genome Editing Tools for Human Disease Model Development and Therapeutic Applications. Genes. 14(2). 483–483. 5 indexed citations
10.
Kim, Narae, et al.. (2023). Precise base editing without unintended indels in human cells and mouse primary myoblasts. Experimental & Molecular Medicine. 55(12). 2586–2595. 5 indexed citations
11.
Lee, Hyunji, et al.. (2023). Trends and prospects in mitochondrial genome editing. Experimental & Molecular Medicine. 55(5). 871–878. 14 indexed citations
12.
Yoon, Hyung Ho, Ara Jo, Seung Eun Lee, et al.. (2022). CRISPR-Cas9 Gene Editing Protects from the A53T-SNCA Overexpression-Induced Pathology of Parkinson's Disease In Vivo. The CRISPR Journal. 5(1). 95–108. 35 indexed citations
13.
Kim, Sojin, Tamrin Chowdhury, Jinhee Ahn, et al.. (2022). Subcellular progression of mesenchymal transition identified by two discrete synchronous cell lines derived from the same glioblastoma. Cellular and Molecular Life Sciences. 79(3). 181–181. 2 indexed citations
14.
Kim, Kyoungmi & Daekee Lee. (2021). ERBB3-dependent AKT and ERK pathways are essential for atrioventricular cushion development in mouse embryos. PLoS ONE. 16(10). e0259426–e0259426. 2 indexed citations
15.
Choi, Jungmin, et al.. (2021). Targeted mutagenesis in mouse cells and embryos using an enhanced prime editor. Genome biology. 22(1). 170–170. 94 indexed citations
16.
Kim, Kyoungmi, et al.. (2014). Happiness improves academic achievement. 20(4). 329–346.
17.
Kim, Kyoungmi, et al.. (2013). Predictors of Intention to Quit Smoking in the Korean Navy Smokers. 13(4). 133–140. 1 indexed citations
18.
Kim, Kyoungmi, Hyunji Lee, David W. Threadgill, & Daekee Lee. (2011). Epiregulin-dependent amphiregulin expression and ERBB2 signaling are involved in luteinizing hormone-induced paracrine signaling pathways in mouse ovary. Biochemical and Biophysical Research Communications. 405(2). 319–324. 22 indexed citations
19.
Kim, Kyoungmi, et al.. (2009). Smoking Cessation Clinics: Expectancy and Cognition. journal of east-west nursing research. 15(2). 141–149.
20.
Kim, Mi Jin, et al.. (2006). Development of a Premature Infant Pain Scale (PIPS).. Journal of Korean Academy of Fundamentals of Nursing. 13(3). 510–519. 2 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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