Sungwon Han

853 citations
25 papers · 645 · h-index 13

Impact in

Papers in

    • Sphingolipid Metabolism and Signaling 4
    • Lipid Membrane Structure and Behavior 3
    • Microbial Metabolic Engineering and Bioproduction 2
    • Glycosylation and Glycoproteins Research 2
    • Lipid metabolism and biosynthesis 4

Sungwon Han

25 papers receiving 639 citations

Peers

Sungwon Han
Comparison fields: 5 of 93
  • Biochemistry 252
  • Cell Biology 157
  • Molecular Biology 403
  • Pollution 34
  • Health, Toxicology and Mutagenesis 39
Replace Michael H. Eley with:
Michael H. Eley United States
Kazuya Yamada Japan
Aaron P. Landry United States
Lingyan Jiang China
Victoria Guixé Chile
Sílvia Sequeira Portugal
Ronald A. Cooper United Kingdom
Martina Chiu Italy
Jan‐Ulrik Dahl United States
Sungwon Han relative to Michael H. Eley United States Michael H. Eley's profile →
Citations per field
00.5×10×15×20.7×
Michael H. Eley · 1×
Citations per year

Countries citing papers authored by Sungwon Han

Since Specialization
Citations

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

Fields of papers citing papers by Sungwon Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014135
2 201185
3 201367
4 201258
5 201556
6 201347
7 201636
8 201920
9 200918
10 201215
11 201314
12 201213
13 200213
14 201911
15 201211
16 201111
17 20219
18 20049
19 20164
20 20233

About Sungwon Han

Sungwon Han is a scholar working on Molecular Biology, Biochemistry, Plant Science, Biomedical Engineering and Cell Biology, having authored 25 papers that have together received 645 indexed citations. Recurring topics across this work include Lipid metabolism and biosynthesis (4 papers), Sphingolipid Metabolism and Signaling (4 papers), Lipid Membrane Structure and Behavior (3 papers), Aluminum toxicity and tolerance in plants and animals (3 papers), Endoplasmic Reticulum Stress and Disease (2 papers), Molecular Junctions and Nanostructures (2 papers), Microbial Metabolic Engineering and Bioproduction (2 papers) and Glycosylation and Glycoproteins Research (2 papers). The work is most often cited by research in Biochemistry (252 citations), Cell Biology (157 citations), Molecular Biology (403 citations), Pollution (34 citations) and Health, Toxicology and Mutagenesis (39 citations). Sungwon Han has collaborated with scholars based in United States, Canada and South Korea. Frequent co-authors include Joel Goodman, Christopher Auger, Vasu D. Appanna, Derk D. Binns, Qiang Gao, Joseph Lemire, Sean C. Thomas, Jin Ye, Gerardo Ulíbarri and Mark J. Graham. Their work appears in journals such as Journal of Biological Chemistry, Cellular Reprogramming, Electrophoresis, PLANT PHYSIOLOGY and Analytical and Bioanalytical Chemistry.

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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