Si Won Lee

62 papers receiving 1.2k citations

Peers

Si Won Lee
Comparison fields: 5 of 101
  • Obstetrics and Gynecology 189
  • Microbiology 8
  • Nutrition and Dietetics 156
  • Pediatrics, Perinatology and Child Health 176
  • Food Science 162
Replace Wen Yao with:
Wen Yao China
Emmanuel Amabebe United Kingdom
R. D. Boyd United States
Siriporn Tuntipopipat Thailand
Elham Hosseini Iran
Akira Hosono Japan
Petya Koleva Canada
Taseer Ahmed Khan Pakistan
R Chierici Italy
Si Won Lee relative to Wen Yao China Wen Yao's profile →
Citations per field
00.5×4.8×
Wen Yao · 1×
Citations per year

Countries citing papers authored by Si Won Lee

Since Specialization
Citations

This map shows the geographic impact of Si 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 Si 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 Si Won Lee more than expected).

Fields of papers citing papers by Si Won Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011276
2 2010101
3 201571
4 201157
5 201253
6 201444
7 200937
8 202034
9 201133
10 201032
11 201830
12 201430
13 201029
14 201828
15 201028
16 201124
17 201422
18 201520
19 201119
20 201217

About Si Won Lee

Si Won Lee is a scholar working on Molecular Biology, Ecology, Pediatrics, Perinatology and Child Health, Public Health, Environmental and Occupational Health and Plant Science, having authored 70 papers that have together received 1.3k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (10 papers), Microbial Community Ecology and Physiology (8 papers), Prenatal Screening and Diagnostics (7 papers), Plant Virus Research Studies (7 papers), Plant and Fungal Interactions Research (5 papers), Probiotics and Fermented Foods (5 papers), Pregnancy and preeclampsia studies (4 papers) and Microbial Metabolism and Applications (4 papers). The work is most often cited by research in Obstetrics and Gynecology (189 citations), Microbiology (8 citations), Nutrition and Dietetics (156 citations), Pediatrics, Perinatology and Child Health (176 citations) and Food Science (162 citations). Si Won Lee has collaborated with scholars based in South Korea, United States and Canada. Frequent co-authors include Hyang Mi An, Nam Joo Ha, Jung Rae Kim, Min Kyeong, Moon Young Kim, Jin Hoon Chung, Do Kyung Lee, Tae‐Young Ahn, Hyun Mee Ryu and You Jung Han. Their work appears in journals such as The Journal of Microbiology, Archives of Pharmacal Research, INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY, The Plant Pathology Journal and Journal of Ultrasound in Medicine.

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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