Yinggui Yang

1.4k total citations · 1 hit paper
23 papers, 1.1k citations indexed

About

Yinggui Yang is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Yinggui Yang has authored 23 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 10 papers in Cancer Research and 5 papers in Oncology. Recurrent topics in Yinggui Yang's work include Cancer-related molecular mechanisms research (8 papers), MicroRNA in disease regulation (4 papers) and RNA modifications and cancer (3 papers). Yinggui Yang is often cited by papers focused on Cancer-related molecular mechanisms research (8 papers), MicroRNA in disease regulation (4 papers) and RNA modifications and cancer (3 papers). Yinggui Yang collaborates with scholars based in China, South Korea and Taiwan. Yinggui Yang's co-authors include Hyog Young Kwon, Ita Novita Sari, Lan Thi Phi, Yun Kyung Lee, Kwang Seock Kim, Sanghyun Lee, Nayoung Jun, Yoseph Toni Wijaya, Chang-Bai Liu and Hu Wang and has published in prestigious journals such as Oncogene, International Journal of Cancer and Bioconjugate Chemistry.

In The Last Decade

Yinggui Yang

23 papers receiving 1.1k citations

Hit Papers

Cancer Stem Cells (CSCs) in Drug Resistance and their The... 2018 2026 2020 2023 2018 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yinggui Yang China 12 690 429 317 128 119 23 1.1k
Min Kyung Ju South Korea 12 691 1.0× 365 0.9× 469 1.5× 100 0.8× 136 1.1× 16 1.1k
Sanchita Rauth United States 18 558 0.8× 378 0.9× 204 0.6× 171 1.3× 118 1.0× 36 962
Sanghyun Lee South Korea 5 610 0.9× 439 1.0× 266 0.8× 82 0.6× 92 0.8× 6 923
Nayoung Jun South Korea 4 607 0.9× 440 1.0× 267 0.8× 81 0.6× 92 0.8× 7 919
Magali Rebucci France 9 509 0.7× 410 1.0× 312 1.0× 72 0.6× 125 1.1× 11 935
Guangchun He China 15 478 0.7× 323 0.8× 297 0.9× 92 0.7× 176 1.5× 25 952
Jianhong Zuo China 15 661 1.0× 289 0.7× 388 1.2× 106 0.8× 105 0.9× 29 1.0k
Bo Tang China 18 522 0.8× 451 1.1× 168 0.5× 116 0.9× 111 0.9× 58 1.1k
Ashish Juvekar United States 11 804 1.2× 468 1.1× 316 1.0× 184 1.4× 131 1.1× 22 1.3k
Jelena Grahovac Serbia 10 471 0.7× 287 0.7× 227 0.7× 126 1.0× 110 0.9× 21 853

Countries citing papers authored by Yinggui Yang

Since Specialization
Citations

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

Fields of papers citing papers by Yinggui Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yinggui Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Yinggui Yang. A scholar is included among the top collaborators of Yinggui 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 Yinggui Yang. Yinggui 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.
Xu, Yaxin, et al.. (2024). CLIP170 inhibits the metastasis and EMT of papillary thyroid cancer through the TGF-β pathway. Medical Oncology. 41(6). 137–137. 1 indexed citations
2.
Zhang, Yuanbin, et al.. (2023). EBV-Associated Hub Genes as Potential Biomarkers for Predicting the Prognosis of Nasopharyngeal Carcinoma. Viruses. 15(9). 1915–1915. 2 indexed citations
3.
Ji, Ziliang, Rui-Jing Lu, Zhong Chen, et al.. (2023). Expression profiling of circular RNA reveals a potential miR-145-5p sponge function of circ-AFF2 and circ-ASAP1 in renal cell carcinoma.. PubMed. 15(1). 82–98. 3 indexed citations
4.
Gong, Ting, Xuedi Zhang, Zhiyong Peng, et al.. (2022). Macrophage-derived exosomal aminopeptidase N aggravates sepsis-induced acute lung injury by regulating necroptosis of lung epithelial cell. Communications Biology. 5(1). 543–543. 39 indexed citations
5.
Zhu, Shimiao, Ziliang Ji, Zhouliang Wu, et al.. (2022). Construction of an Epithelial-Mesenchymal Transition-Related Model for Clear Cell Renal Cell Carcinoma Prognosis Prediction. Disease Markers. 2022. 1–15. 1 indexed citations
6.
Yang, Yinggui, et al.. (2022). [Advances in research of Musashi2 in solid tumors].. PubMed. 42(3). 448–456. 1 indexed citations
7.
Leng, Yun, Can Zhao, Guoliang Yan, et al.. (2021). Ghrelin enhances cisplatin sensitivity in HO-8910 PM human ovarian cancer cells. Journal of Ovarian Research. 14(1). 162–162. 2 indexed citations
8.
Chen, Zheng, et al.. (2021). [Photothermal effect of nano-copper sulfide against tongue squamous cell carcinoma].. PubMed. 41(12). 1843–1849. 1 indexed citations
9.
Sari, Ita Novita, Yinggui Yang, Yoseph Toni Wijaya, et al.. (2020). AMD1 is required for the maintenance of leukemic stem cells and promotes chronic myeloid leukemic growth. Oncogene. 40(3). 603–617. 11 indexed citations
10.
Gong, Ting, Xin Li, Hyog Young Kwon, et al.. (2020). microRNA-219-5p targets NEK6 to inhibit hepatocellular carcinoma progression.. American Journal of Translational Research. 12(11). 7528–7541. 12 indexed citations
11.
Phi, Lan Thi, Yoseph Toni Wijaya, Ita Novita Sari, et al.. (2019). <p>20(R)-Ginsenoside Rg3 Influences Cancer Stem Cell Properties and the Epithelial-Mesenchymal Transition in Colorectal Cancer via the SNAIL Signaling Axis</p>. OncoTargets and Therapy. Volume 12. 10885–10895. 22 indexed citations
12.
Kim, Kwang Seock, Dongjun Jeong, Ita Novita Sari, et al.. (2019). miR551b Regulates Colorectal Cancer Progression by Targeting the ZEB1 Signaling Axis. Cancers. 11(5). 735–735. 3 indexed citations
14.
Phi, Lan Thi, Yoseph Toni Wijaya, Ita Novita Sari, et al.. (2018). The anti‐metastatic effect of ginsenoside Rb2 in colorectal cancer in an EGFR/SOX2‐dependent manner. Cancer Medicine. 7(11). 5621–5631. 31 indexed citations
15.
Yang, Yinggui, Young Wha Koh, Ita Novita Sari, et al.. (2018). Interferon‐induced transmembrane protein 1‐mediated EGFR/SOX2 signaling axis is essential for progression of non‐small cell lung cancer. International Journal of Cancer. 144(8). 2020–2032. 21 indexed citations
16.
Yang, Yinggui, et al.. (2016). Tetraspanins: Spanning from solid tumors to hematologic malignancies. Experimental Hematology. 44(5). 322–328. 34 indexed citations
17.
Sari, Ita Novita, Yinggui Yang, Lan Thi Phi, et al.. (2016). Interferon-induced transmembrane protein 1 (IFITM1) is required for the progression of colorectal cancer. Oncotarget. 7(52). 86039–86050. 35 indexed citations
18.
Wang, Hu, et al.. (2016). Highly Efficient Delivery of Functional Cargoes by a Novel Cell-Penetrating Peptide Derived from SP140-Like Protein. Bioconjugate Chemistry. 27(5). 1373–1381. 28 indexed citations
19.
H, Shi, et al.. (2001). [The clinical significance of detection of urinary ceruloplasmin in type 2 diabetes].. PubMed. 40(12). 823–5. 3 indexed citations
20.
Yang, Yinggui, et al.. (1997). Spontaneous remission in acute myelogenous leukemia: a case report.. PubMed. 59(2). 121–5. 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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