Ha Won Lee

1.0k citations
15 papers · 483 · h-index 10

Impact in

Papers in

    • Bacterial biofilms and quorum sensing 2
    • Single-cell and spatial transcriptomics 1
    • Renal Diseases and Glomerulopathies 5
    • Chronic Kidney Disease and Diabetes 2

Ha Won Lee

15 papers receiving 480 citations

Peers

Ha Won Lee
Comparison fields: 5 of 85
  • Nephrology 93
  • Orthopedics and Sports Medicine 54
  • Cancer Research 56
  • Endocrine and Autonomic Systems 25
  • Molecular Biology 210
Replace Jin-Hyun Woo with:
Jin-Hyun Woo South Korea
Rainer Finke Germany
Gabrielle K. Steinl United States
Stephanie Denk Germany
K Chihara Japan
Stefanie Fischer Switzerland
Jianqiu Xiao United States
Anna Ciampolillo Italy
Betsy Evans United Kingdom
Lara Pizurki Switzerland
Ha Won Lee relative to Jin-Hyun Woo South Korea Jin-Hyun Woo's profile →
Citations per field
00.5×4.8×
Jin-Hyun Woo · 1×
Citations per year

Countries citing papers authored by Ha Won Lee

Since Specialization
Citations

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

Fields of papers citing papers by Ha Won Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 2013183
2 201680
3 201549
4 201233
5 201831
6 201630
7 201621
8 201921
9 201710
10 201310
11 20235
12 20174
13 20143
14 20242
15 20251

About Ha Won Lee

Ha Won Lee is a scholar working on Molecular Biology, Nephrology, Pulmonary and Respiratory Medicine, Oncology and Epidemiology, having authored 15 papers that have together received 483 indexed citations. Recurring topics across this work include Renal Diseases and Glomerulopathies (5 papers), Cystic Fibrosis Research Advances (2 papers), Bacterial biofilms and quorum sensing (2 papers), Neonatal Respiratory Health Research (2 papers), Adipokines, Inflammation, and Metabolic Diseases (2 papers), Chronic Kidney Disease and Diabetes (2 papers), Single-cell and spatial transcriptomics (1 paper) and MicroRNA in disease regulation (1 paper). The work is most often cited by research in Nephrology (93 citations), Orthopedics and Sports Medicine (54 citations), Cancer Research (56 citations), Endocrine and Autonomic Systems (25 citations) and Molecular Biology (210 citations). Ha Won Lee has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Vineet Gupta, Gérard Karsenty, Ronald A. DePinho, Yusuf A. Hannun, X. Edward Guo, Christopher J. Clarke, Emilio Arteaga‐Solis, Mathieu Ferron, Daisuke Kajimura and Bin Zhou. Their work appears in journals such as Cell Metabolism, Journal of the American Society of Nephrology, Scientific Reports, Cellular Physiology and Biochemistry and Genes & Diseases.

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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