Gwang Lee

10.9k total citations · 2 hit papers
159 papers, 8.7k citations indexed

About

Gwang Lee is a scholar working on Molecular Biology, Genetics and Neurology. According to data from OpenAlex, Gwang Lee has authored 159 papers receiving a total of 8.7k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Molecular Biology, 18 papers in Genetics and 18 papers in Neurology. Recurrent topics in Gwang Lee's work include Machine Learning in Bioinformatics (29 papers), Mesenchymal stem cell research (16 papers) and RNA and protein synthesis mechanisms (15 papers). Gwang Lee is often cited by papers focused on Machine Learning in Bioinformatics (29 papers), Mesenchymal stem cell research (16 papers) and RNA and protein synthesis mechanisms (15 papers). Gwang Lee collaborates with scholars based in South Korea, United States and Japan. Gwang Lee's co-authors include Balachandran Manavalan, Tae Hwan Shin, Shaherin Basith, Phil Hyu Lee, Oh Young Bang, Jin Soo Lee, Izumu Saito, Sangdun Choi, Myeong Ok Kim and Leyi Wei and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and SHILAP Revista de lepidopterología.

In The Last Decade

Gwang Lee

154 papers receiving 8.5k citations

Hit Papers

Autologous mesenchymal stem cell transplantation in strok... 1995 2026 2005 2015 2005 1995 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gwang Lee South Korea 49 5.2k 1.2k 832 678 648 159 8.7k
Daehee Hwang South Korea 57 7.8k 1.5× 414 0.4× 876 1.1× 191 0.3× 2.0k 3.1× 232 13.7k
Ye Zhang China 43 4.6k 0.9× 468 0.4× 246 0.3× 191 0.3× 1.1k 1.7× 437 9.8k
Spencer B. Gibson Canada 53 7.8k 1.5× 798 0.7× 401 0.5× 106 0.2× 2.2k 3.5× 163 13.0k
Rainer Bischoff Netherlands 56 6.4k 1.2× 268 0.2× 297 0.4× 202 0.3× 941 1.5× 348 11.9k
Gang Lü China 55 5.6k 1.1× 766 0.7× 636 0.8× 56 0.1× 2.1k 3.3× 380 12.1k
Jake Y. Chen United States 48 6.4k 1.2× 600 0.5× 1.1k 1.4× 74 0.1× 854 1.3× 223 14.6k
Xuejun Li China 45 3.5k 0.7× 484 0.4× 307 0.4× 100 0.1× 1.5k 2.3× 371 7.8k
Gang Wang China 62 5.8k 1.1× 611 0.5× 326 0.4× 105 0.2× 1.8k 2.8× 679 15.2k
Yasuhiro Yamada Japan 63 9.8k 1.9× 361 0.3× 620 0.7× 91 0.1× 1.8k 2.8× 482 16.7k
Kyong‐Tai Kim South Korea 53 5.1k 1.0× 225 0.2× 1.2k 1.5× 109 0.2× 427 0.7× 305 9.4k

Countries citing papers authored by Gwang Lee

Since Specialization
Citations

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

Fields of papers citing papers by Gwang Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gwang Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Gwang Lee. A scholar is included among the top collaborators of Gwang Lee 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 Gwang Lee. Gwang Lee 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.
2.
Basith, Shaherin, et al.. (2024). mHPpred: Accurate identification of peptide hormones using multi-view feature learning. Computers in Biology and Medicine. 183. 109297–109297. 2 indexed citations
3.
Basith, Shaherin, Balachandran Manavalan, & Gwang Lee. (2023). Unveiling local and global conformational changes and allosteric communications in SOD1 systems using molecular dynamics simulation and network analyses. Computers in Biology and Medicine. 168. 107688–107688. 3 indexed citations
5.
Park, Jun Sung, Kamran Saeed, Myeung Hoon Jo, et al.. (2022). LDHB Deficiency Promotes Mitochondrial Dysfunction Mediated Oxidative Stress and Neurodegeneration in Adult Mouse Brain. Antioxidants. 11(2). 261–261. 25 indexed citations
6.
Basith, Shaherin, Md Mehedi Hasan, Gwang Lee, Leyi Wei, & Balachandran Manavalan. (2021). Integrative machine learning framework for the identification of cell-specific enhancers from the human genome. Briefings in Bioinformatics. 22(6). 52 indexed citations
7.
Manavalan, Balachandran, Shaherin Basith, Tae Hwan Shin, et al.. (2019). 4mCpred-EL: An Ensemble Learning Framework for Identification of DNA N4-Methylcytosine Sites in the Mouse Genome. Cells. 8(11). 1332–1332. 83 indexed citations
8.
Lee, Sung-Ju, et al.. (2019). <p>Enhanced anti-tumor immunotherapy by silica-coated magnetic nanoparticles conjugated with ovalbumin</p>. International Journal of Nanomedicine. Volume 14. 8235–8249. 17 indexed citations
9.
Manavalan, Balachandran, Shaherin Basith, Tae Hwan Shin, Leyi Wei, & Gwang Lee. (2018). mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation. Bioinformatics. 35(16). 2757–2765. 221 indexed citations
10.
Shin, Tae Hwan, Hyoun‐Ah Kim, Ju‐Yang Jung, et al.. (2017). Analysis of the free fatty acid metabolome in the plasma of patients with systemic lupus erythematosus and fever. Metabolomics. 14(1). 14–14. 62 indexed citations
11.
Shin, Tae Hwan, Seungah Lee, Da Yeon Lee, et al.. (2017). Quality and freshness of human bone marrow-derived mesenchymal stem cells decrease over time after trypsinization and storage in phosphate-buffered saline. Scientific Reports. 7(1). 1106–1106. 23 indexed citations
12.
Shin, Tae Hwan, et al.. (2016). Restoration of Polyamine Metabolic Patterns in In Vivo and In Vitro Model of Ischemic Stroke following Human Mesenchymal Stem Cell Treatment. Stem Cells International. 2016(1). 4612531–4612531. 20 indexed citations
13.
Lee, Gwang, et al.. (2012). A Study on Pilot-test of the CCTV Fog Visibility Measurement System. 719–721.
14.
Lee, Kyungho, et al.. (2011). A Study On 3D Design Model-based-visualization System to Support Pipe Maintenance. The Twenty-first International Offshore and Polar Engineering Conference. 1 indexed citations
15.
Um, Ji Won, Jihwan Song, Iksoo Jeon, et al.. (2010). Formation of parkin aggregates and enhanced PINK1 accumulation during the pathogenesis of Parkinson’s disease. Biochemical and Biophysical Research Communications. 393(4). 824–828. 17 indexed citations
16.
Um, Ji Won, et al.. (2009). Molecular interaction between parkin and PINK1 in mammalian neuronal cells. Molecular and Cellular Neuroscience. 40(4). 421–432. 52 indexed citations
17.
Kim, Sung‐Hoon, Wooyoung Shim, Je Hyun Bae, et al.. (2009). Bandgap engineered reverse type-I CdTe/InP/ZnS core–shell nanocrystals for the near-infrared. Chemical Communications. 1267–1267. 26 indexed citations
18.
Krishnan, Jayalakshmi, Kumar Selvarajoo, Masa Tsuchiya, Gwang Lee, & Sangdun Choi. (2007). Toll-like receptor signal transduction. Experimental & Molecular Medicine. 39(4). 421–438. 188 indexed citations
19.
Paik, Man‐Jeong, Ki Ho Park, Joong‐Jean Park, et al.. (2007). Patterns of Plasma Fatty Acids in Rat Models with Adenovirus Infection. BMB Reports. 40(1). 119–124. 9 indexed citations
20.
Cheon, Sang‐Myung, et al.. (2007). Inclusion Body Formation and Apoptotic Cell Death in the Human Neural Stem Cells HB1.F3 Following Gene Transfection of Alpha-Synuclein and Synphilin-1. Journal of the Korean Neurological Association. 25(3). 344–352. 1 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026