Younggwang Kim

993 total citations
10 papers, 632 citations indexed

About

Younggwang Kim is a scholar working on Molecular Biology, Neurology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Younggwang Kim has authored 10 papers receiving a total of 632 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 1 paper in Neurology and 1 paper in Pulmonary and Respiratory Medicine. Recurrent topics in Younggwang Kim's work include CRISPR and Genetic Engineering (7 papers), RNA and protein synthesis mechanisms (5 papers) and RNA Research and Splicing (2 papers). Younggwang Kim is often cited by papers focused on CRISPR and Genetic Engineering (7 papers), RNA and protein synthesis mechanisms (5 papers) and RNA Research and Splicing (2 papers). Younggwang Kim collaborates with scholars based in South Korea, United States and Ethiopia. Younggwang Kim's co-authors include Seokjoong Kim, Hui Kwon Kim, Jae Woo Choi, Seonwoo Min, Sungroh Yoon, Jinman Park, Sungtae Lee, Sangeun Lee, Jung Yoon Bae and Dongmin Jung and has published in prestigious journals such as Nature Biotechnology, Science Advances and Journal of Alzheimer s Disease.

In The Last Decade

Younggwang Kim

9 papers receiving 622 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Younggwang Kim South Korea	6	593	116	51	50	36	10	632
Sungtae Lee South Korea	7	660 1.1×	142 1.2×	65 1.3×	70 1.4×	43 1.2×	11	690
Lea B. Witkowsky United States	5	583 1.0×	93 0.8×	56 1.1×	77 1.5×	50 1.4×	5	611
Saskia Gressel Germany	6	773 1.3×	67 0.6×	55 1.1×	49 1.0×	36 1.0×	7	801
Gue‐Ho Hwang South Korea	14	597 1.0×	173 1.5×	63 1.2×	69 1.4×	32 0.9×	23	631
Sudharshan Rangarajan United States	2	579 1.0×	115 1.0×	50 1.0×	69 1.4×	69 1.9×	2	601
Yayoi Kunihiro Japan	7	541 0.9×	225 1.9×	55 1.1×	50 1.0×	54 1.5×	8	619
Alexander Strong United Kingdom	3	524 0.9×	124 1.1×	35 0.7×	83 1.7×	44 1.2×	3	556
Bingbing He China	6	484 0.8×	121 1.0×	32 0.6×	53 1.1×	17 0.5×	13	528
Joonsun Lee South Korea	7	496 0.8×	90 0.8×	60 1.2×	55 1.1×	44 1.2×	8	526
Changyang Zhou China	11	665 1.1×	184 1.6×	59 1.2×	47 0.9×	23 0.6×	16	707

Countries citing papers authored by Younggwang Kim

Since Specialization

Citations

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

Fields of papers citing papers by Younggwang Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Younggwang Kim

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

Kim, Younggwang, et al.. (2025). In vivo delivery systems for CRISPR genome editing: Viral and non-viral carriers. Applied Physics Reviews. 12(2). 4 indexed citations

Kim, Younggwang, Min Ki Kim, & Sanghun Lee. (2025). Comparative microbiome analysis of paired mucosal and fecal samples in Korean colorectal cancer patients. Frontiers in Oncology. 15. 1578861–1578861.

Kim, Younggwang, et al.. (2024). Saturation profiling of drug-resistant genetic variants using prime editing. Nature Biotechnology. 43(9). 1471–1484. 11 indexed citations

Kim, Younggwang, Seung‐Ho Lee, Jinman Park, et al.. (2022). High-throughput functional evaluation of human cancer-associated mutations using base editors. Nature Biotechnology. 40(6). 874–884. 39 indexed citations

Kim, Hui Kwon, Sungtae Lee, Younggwang Kim, et al.. (2020). Sequence-specific prediction of the efficiencies of adenine and cytosine base editors. Nature Biotechnology. 38(9). 1037–1043. 81 indexed citations

Kim, Hui Kwon, Sungtae Lee, Younggwang Kim, et al.. (2020). High-throughput analysis of the activities of xCas9, SpCas9-NG and SpCas9 at matched and mismatched target sequences in human cells. Nature Biomedical Engineering. 4(1). 111–124. 106 indexed citations

Kim, Hui Kwon, Younggwang Kim, Sungtae Lee, et al.. (2019). SpCas9 activity prediction by DeepSpCas9, a deep learning–based model with high generalization performance. Science Advances. 5(11). eaax9249–eaax9249. 140 indexed citations

Min, Seonwoo, et al.. (2019). DeepCpf1: Deep learning-based prediction ofCRISPR-Cpf1 activity at endogenous sites. Proceedings for Annual Meeting of The Japanese Pharmacological Society. 92(0). JKL–5. 1 indexed citations

Kim, Hui Kwon, Seonwoo Min, Jae Woo Choi, et al.. (2018). Deep learning improves prediction of CRISPR–Cpf1 guide RNA activity. Nature Biotechnology. 36(3). 239–241. 245 indexed citations

10.

Kim, Younggwang, Dong-Kyun Lee, Kyoo Ho Cho, et al.. (2016). Cognitive and Neuroanatomical Correlates in Early Versus Late Onset Parkinson’s Disease Dementia. Journal of Alzheimer s Disease. 55(2). 485–495. 5 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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