Ki-Won Oh

2.9k total citations
129 papers, 2.2k citations indexed

About

Ki-Won Oh is a scholar working on Plant Science, Endocrinology, Diabetes and Metabolism and Molecular Biology. According to data from OpenAlex, Ki-Won Oh has authored 129 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Plant Science, 31 papers in Endocrinology, Diabetes and Metabolism and 24 papers in Molecular Biology. Recurrent topics in Ki-Won Oh's work include Soybean genetics and cultivation (16 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (13 papers) and Liver Disease Diagnosis and Treatment (12 papers). Ki-Won Oh is often cited by papers focused on Soybean genetics and cultivation (16 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (13 papers) and Liver Disease Diagnosis and Treatment (12 papers). Ki-Won Oh collaborates with scholars based in South Korea, Ghana and United Kingdom. Ki-Won Oh's co-authors include Won‐Young Lee, Eun‐Jung Rhee, Cheol‐Young Park, Se Eun Park, Sun-Woo Kim, Sung‐Woo Park, Seok‐Woo Hong, Jinmi Lee, Chan‐Hee Jung and Heung‐Woo Park and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Ki-Won Oh

120 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ki-Won Oh South Korea 27 692 689 581 395 369 129 2.2k
Óscar Pérez‐Méndez Mexico 23 290 0.4× 547 0.8× 410 0.7× 327 0.8× 429 1.2× 127 1.9k
Yan‐Xiao Ji China 29 1.5k 2.1× 495 0.7× 1.4k 2.4× 441 1.1× 225 0.6× 50 3.1k
Monica Gomaraschi Italy 28 267 0.4× 798 1.2× 581 1.0× 430 1.1× 933 2.5× 64 2.3k
Yong Ki Kim South Korea 24 267 0.4× 674 1.0× 384 0.7× 218 0.6× 349 0.9× 88 2.0k
Mingfeng Xia China 27 1.5k 2.1× 913 1.3× 747 1.3× 333 0.8× 292 0.8× 98 2.7k
Yoshitaka Kumon Japan 27 224 0.3× 354 0.5× 549 0.9× 281 0.7× 460 1.2× 95 2.3k
Chunxiao Yu China 33 455 0.7× 1.0k 1.5× 823 1.4× 135 0.3× 266 0.7× 103 2.6k
Guanliang Chen Japan 16 621 0.9× 524 0.8× 429 0.7× 149 0.4× 294 0.8× 25 1.6k
Yang Song China 25 498 0.7× 355 0.5× 742 1.3× 110 0.3× 389 1.1× 68 2.3k
Gloria Formoso Italy 27 280 0.4× 631 0.9× 661 1.1× 385 1.0× 297 0.8× 59 2.2k

Countries citing papers authored by Ki-Won Oh

Since Specialization
Citations

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

Fields of papers citing papers by Ki-Won Oh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ki-Won Oh. 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 Ki-Won Oh. The network helps show where Ki-Won Oh may publish in the future.

Co-authorship network of co-authors of Ki-Won Oh

This figure shows the co-authorship network connecting the top 25 collaborators of Ki-Won Oh. A scholar is included among the top collaborators of Ki-Won Oh 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 Ki-Won Oh. Ki-Won Oh 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
2.
Kabange, Nkulu Rolly, Dong-Soo Park, Youngho Kwon, et al.. (2023). Rice (Oryza sativa L.) Grain Size, Shape, and Weight-Related QTLs Identified Using GWAS with Multiple GAPIT Models and High-Density SNP Chip DNA Markers. Plants. 12(23). 4044–4044. 3 indexed citations
3.
Kabange, Nkulu Rolly, Youngho Kwon, So-Myeong Lee, et al.. (2023). Mitigating Greenhouse Gas Emissions from Crop Production and Management Practices, and Livestock: A Review. Sustainability. 15(22). 15889–15889. 11 indexed citations
4.
Lee, So-Myeong, Nkulu Rolly Kabange, Ju-Won Kang, et al.. (2023). Identifying QTLs Related to Grain Filling Using a Doubled Haploid Rice (Oryza sativa L.) Population. Agronomy. 13(3). 912–912. 1 indexed citations
5.
Kwon, Youngho, So-Myeong Lee, Nkulu Rolly Kabange, et al.. (2023). Loss-of-function gs3 allele decreases methane emissions and increases grain yield in rice. Nature Climate Change. 13(12). 1329–1333. 23 indexed citations
7.
Lee, Ji Yoon, Ju-Won Kang, Hyunggon Mang, et al.. (2022). A Novel Locus for Bakanae Disease Resistance, qBK4T, Identified in Rice. Agronomy. 12(10). 2567–2567. 10 indexed citations
8.
Lee, Myoung-Hee, et al.. (2021). Agricultural and Quality Characteristics in Recombinant Inbred Lines (RILs) Population in Perilla (Perilla frutescens). The Korean Journal of Crop Science. 66(3). 248–255. 1 indexed citations
9.
Asekova, Sovetgul, Krishnanand P. Kulkarni, Ki-Won Oh, et al.. (2018). Analysis of molecular variance and population structure of sesame (Sesamum indicum L.) genotypes using SSR markers. 25–25. 1 indexed citations
10.
Lee, Jinmi, Seok‐Woo Hong, Se Eun Park, et al.. (2015). AMP-activated protein kinase suppresses the expression of LXR/SREBP-1 signaling-induced ANGPTL8 in HepG2 cells. Molecular and Cellular Endocrinology. 414. 148–155. 59 indexed citations
11.
Oh, Ki-Won, et al.. (2011). A Case of Enterovirus 71 Infection Presented with Acute Flaccid Paralysis. 19(1). 61–66. 1 indexed citations
12.
Park, Sun Min, et al.. (2008). Correlation between Cephalhematomas and Intracranial Hematomas. Neonatal Medicine. 15(2). 160–165. 1 indexed citations
13.
Jung, Chan‐Hee, Eun‐Jung Rhee, Byung Jin Kim, et al.. (2006). Association between two SNPs (+45T>G and +276G>T) of the adiponectin gene and coronary artery diseases. The Korean Journal of Internal Medicine. 70(4). 393–401. 1 indexed citations
14.
Lee, Eunjung, Chan‐Hee Jung, Byung Jin Kim, et al.. (2006). The association of KLOTHO gene polymorphism with coronary artery disease in Korean subjects. The Korean Journal of Internal Medicine. 70(3). 268–276. 1 indexed citations
15.
Kim, Jong Yeop, In‐Kyung Jeong, Cheol‐Young Park, et al.. (2005). The relationship of adiponectin, leptin and ghrelin to insulin resistance and cardiovascular risk factors in human obesity. The Korean Journal of Internal Medicine. 69(6). 631–641. 15 indexed citations
16.
Oh, Ki-Won, Eunsoon Oh, Jee‐Aee Im, et al.. (2003). The relationship between urinary sodium excretion and bone mineral metabolism of climacteric women in Korea.. The Korean Journal of Internal Medicine. 65(4). 436–442. 2 indexed citations
17.
Oh, Ki-Won, et al.. (2003). Serum Insulin-Like Growth Factor I and Its Relating Factors in Healthy Korean Adults Aged over 40 Years.. Gajeong yihag hoeji. 24(1). 51–57. 1 indexed citations
18.
Jung, Chan-Sik, et al.. (2002). Effect of Seeding Date on Growth Habit and Pod Setting of Peanut in Southern Korea. The Korean Journal of Crop Science. 47(5). 374–378. 1 indexed citations
19.
Oh, Ki-Won, et al.. (2000). Determination of Seed Lipid and Protein Contents in Perilla and Peanut by Near-Infrared Reflectance Spectroscopy. The Korean Journal of Crop Science. 45(5). 339–342. 5 indexed citations
20.
Kim, Hack-Seang & Ki-Won Oh. (1994). Effect of Ginseng Total Saponin on the Development of Psychic and Physical Dependence on Nalbuphine. Biomolecules & Therapeutics. 2(4). 316–321. 2 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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