Won‐Mo Yang

611 total citations
21 papers, 486 citations indexed

About

Won‐Mo Yang is a scholar working on Molecular Biology, Cancer Research and Physiology. According to data from OpenAlex, Won‐Mo Yang has authored 21 papers receiving a total of 486 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 13 papers in Cancer Research and 6 papers in Physiology. Recurrent topics in Won‐Mo Yang's work include MicroRNA in disease regulation (13 papers), Cancer-related molecular mechanisms research (11 papers) and Circular RNAs in diseases (8 papers). Won‐Mo Yang is often cited by papers focused on MicroRNA in disease regulation (13 papers), Cancer-related molecular mechanisms research (11 papers) and Circular RNAs in diseases (8 papers). Won‐Mo Yang collaborates with scholars based in South Korea, United States and Australia. Won‐Mo Yang's co-authors include Wan Lee, Hyo‐Jin Jeong, Seung‐Yoon Park, Joo‐Hyun Nam, Young‐Won Chin, Hyo Won Jung, Woo Kyung Kim, Kellen Cristina da Cruz Rodrigues, Hyon Lee and Aykut Göktürk Üner and has published in prestigious journals such as Nature Communications, PLoS ONE and Diabetes.

In The Last Decade

Won‐Mo Yang

21 papers receiving 482 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Won‐Mo Yang South Korea 11 316 308 86 62 48 21 486
Hongyan Ling China 12 463 1.5× 426 1.4× 99 1.2× 80 1.3× 62 1.3× 27 717
Jacek Turyn Poland 13 244 0.8× 135 0.4× 88 1.0× 65 1.0× 32 0.7× 21 448
Zhen He China 10 217 0.7× 97 0.3× 70 0.8× 56 0.9× 40 0.8× 25 454
Liangjie Jia China 5 213 0.7× 95 0.3× 107 1.2× 96 1.5× 60 1.3× 8 436
Xiaoqiang Tian China 10 243 0.8× 171 0.6× 65 0.8× 17 0.3× 29 0.6× 15 431
Filippo Zeni Italy 5 169 0.5× 113 0.4× 77 0.9× 37 0.6× 20 0.4× 7 423
Julia S. Jacobs United States 11 251 0.8× 133 0.4× 114 1.3× 79 1.3× 36 0.8× 15 425
Austin G. Hester United States 8 161 0.5× 141 0.5× 87 1.0× 61 1.0× 46 1.0× 14 398
Linjie He China 7 223 0.7× 98 0.3× 43 0.5× 30 0.5× 24 0.5× 12 341
Yanyun Fu China 9 237 0.8× 60 0.2× 135 1.6× 72 1.2× 52 1.1× 13 397

Countries citing papers authored by Won‐Mo Yang

Since Specialization
Citations

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

Fields of papers citing papers by Won‐Mo Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Won‐Mo Yang. 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 Won‐Mo Yang. The network helps show where Won‐Mo Yang may publish in the future.

Co-authorship network of co-authors of Won‐Mo Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Won‐Mo Yang. A scholar is included among the top collaborators of Won‐Mo Yang 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 Won‐Mo Yang. Won‐Mo Yang 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.
Pittala, Srinivas, Dhanush Haspula, Yinghong Cui, et al.. (2024). G12/13-mediated signaling stimulates hepatic glucose production and has a major impact on whole body glucose homeostasis. Nature Communications. 15(1). 9996–9996. 3 indexed citations
2.
Rodrigues, Kellen Cristina da Cruz, Seung Chan Kim, Aykut Göktürk Üner, et al.. (2024). LRP1 in GABAergic neurons is a key link between obesity and memory function. Molecular Metabolism. 84. 101941–101941. 4 indexed citations
3.
Kim, Young‐Bum, et al.. (2024). 1540-P: LRP1 in GABAergic Neurons Is a Key Link between Obesity and Memory Function. Diabetes. 73(Supplement_1). 1 indexed citations
4.
Yang, Won‐Mo, et al.. (2022). ROCK1 regulates insulin secretion from β-cells. Molecular Metabolism. 66. 101625–101625. 2 indexed citations
5.
Yang, Won‐Mo, et al.. (2018). Saturated fatty acids-induced miR-424–5p aggravates insulin resistance via targeting insulin receptor in hepatocytes. Biochemical and Biophysical Research Communications. 503(3). 1587–1593. 32 indexed citations
6.
Yang, Won‐Mo, et al.. (2017). Data on the decreased expression of FOXO1 by miR-1271 in HepG2 hepatocytes. Data in Brief. 15. 800–804. 5 indexed citations
7.
Yang, Won‐Mo, et al.. (2017). Data on the expression and insulin-stimulated phosphorylation of IRS-1 by miR-96 in L6-GLUT4myc myocytes. Data in Brief. 15. 728–732. 3 indexed citations
8.
Yang, Won‐Mo, et al.. (2017). Data on the expression of PEPCK in HepG2 hepatocytes transfected with miR-195. Data in Brief. 15. 747–751. 6 indexed citations
9.
Nam, Joo‐Hyun, et al.. (2017). Spirodela polyrhiza extract modulates the activation of atopic dermatitis-related ion channels, Orai1 and TRPV3, and inhibits mast cell degranulation. Pharmaceutical Biology. 55(1). 1324–1329. 21 indexed citations
10.
Yang, Won‐Mo, et al.. (2016). MicroRNA expression analysis in the liver of high fat diet-induced obese mice. Data in Brief. 9. 1155–1159. 12 indexed citations
11.
Yang, Won‐Mo, et al.. (2016). Induction of miR-96 by Dietary Saturated Fatty Acids Exacerbates Hepatic Insulin Resistance through the Suppression of INSR and IRS-1. PLoS ONE. 11(12). e0169039–e0169039. 52 indexed citations
12.
Yang, Won‐Mo, et al.. (2016). MiR-1271 upregulated by saturated fatty acid palmitate provokes impaired insulin signaling by repressing INSR and IRS-1 expression in HepG2 cells. Biochemical and Biophysical Research Communications. 478(4). 1786–1791. 25 indexed citations
13.
Yang, Won‐Mo, et al.. (2016). Data for differentially expressed microRNAs in saturated fatty acid palmitate-treated HepG2 cells. Data in Brief. 9. 996–999. 3 indexed citations
14.
15.
Yang, Won‐Mo, et al.. (2015). Obesity‐induced miR‐15b is linked causally to the development of insulin resistance through the repression of the insulin receptor in hepatocytes. Molecular Nutrition & Food Research. 59(11). 2303–2314. 74 indexed citations
16.
Yang, Won‐Mo, Hyo‐Jin Jeong, Seung‐Yoon Park, & Wan Lee. (2014). Induction of miR‐29a by saturated fatty acids impairs insulin signaling and glucose uptake through translational repression of IRS‐1 in myocytes. FEBS Letters. 588(13). 2170–2176. 84 indexed citations
17.
Yang, Won‐Mo & Wan Lee. (2014). CTRP5 ameliorates palmitate-induced apoptosis and insulin resistance through activation of AMPK and fatty acid oxidation. Biochemical and Biophysical Research Communications. 452(3). 715–721. 21 indexed citations
18.
Yang, Won‐Mo, Hyo‐Jin Jeong, Seung‐Yoon Park, & Wan Lee. (2014). Saturated fatty acid‐induced miR‐195 impairs insulin signaling and glycogen metabolism in HepG2 cells. FEBS Letters. 588(21). 3939–3946. 62 indexed citations
19.
Park, Seung‐Yoon, Hyo‐Jin Jeong, Won‐Mo Yang, & Wan Lee. (2013). Implications of microRNAs in the pathogenesis of diabetes. Archives of Pharmacal Research. 36(2). 154–166. 33 indexed citations
20.
Jeong, Hyo‐Jin, Seung‐Yoon Park, Won‐Mo Yang, & Wan Lee. (2013). The induction of miR-96 by mitochondrial dysfunction causes impaired glycogen synthesis through translational repression of IRS-1 in SK-Hep1 cells. Biochemical and Biophysical Research Communications. 434(3). 503–508. 35 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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