Shilong Ying

838 total citations
26 papers, 647 citations indexed

About

Shilong Ying is a scholar working on Molecular Biology, Cell Biology and Molecular Medicine. According to data from OpenAlex, Shilong Ying has authored 26 papers receiving a total of 647 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 6 papers in Cell Biology and 5 papers in Molecular Medicine. Recurrent topics in Shilong Ying's work include Fibroblast Growth Factor Research (5 papers), Curcumin's Biomedical Applications (5 papers) and Genomics, phytochemicals, and oxidative stress (4 papers). Shilong Ying is often cited by papers focused on Fibroblast Growth Factor Research (5 papers), Curcumin's Biomedical Applications (5 papers) and Genomics, phytochemicals, and oxidative stress (4 papers). Shilong Ying collaborates with scholars based in China and Tunisia. Shilong Ying's co-authors include Guang Liang, Hongchuan Jin, Xian Wang, Liyuan Zhu, Weiqian Chen, Xi Chen, Zhiguo Liu, Jiansong Ji, Peng Zou and Shulin Yang and has published in prestigious journals such as Blood, Scientific Reports and Journal of Medicinal Chemistry.

In The Last Decade

Shilong Ying

25 papers receiving 643 citations

Peers

Shilong Ying
Shilong Ying
Citations per year, relative to Shilong Ying Shilong Ying (= 1×) peers Tongke Chen

Countries citing papers authored by Shilong Ying

Since Specialization
Citations

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

Fields of papers citing papers by Shilong Ying

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shilong Ying

This figure shows the co-authorship network connecting the top 25 collaborators of Shilong Ying. A scholar is included among the top collaborators of Shilong Ying 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 Shilong Ying. Shilong Ying 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.
Zhang, Lulu, Shilong Ying, Fang Fang, et al.. (2025). Cumulative burden of myelodysplasia-related gene mutations is associated with poor leukemia-free survival in ELN-2022 favorable-risk AML. Blood. 146(Supplement 1). 7025–7025.
2.
Ying, Shilong, et al.. (2024). Artificial Intelligence-Driven Precision Medicine: Multi-Omics and Spatial Multi-Omics Approaches in Diffuse Large B-Cell Lymphoma (DLBCL). Frontiers in Bioscience-Landmark. 29(12). 404–404. 9 indexed citations
3.
Ying, Shilong, et al.. (2024). Selective and Orally Bioavailable c-Met PROTACs for the Treatment of c-Met-Addicted Cancer. Journal of Medicinal Chemistry. 67(19). 17053–17069. 2 indexed citations
4.
Hu, Xinyang, Ting Sun, Chaoqun Wang, et al.. (2023). Golgi-protein 73 facilitates vimentin polymerization in hepatocellular carcinoma. International Journal of Biological Sciences. 19(12). 3694–3708. 4 indexed citations
5.
Zhu, Yiran, Bingluo Zhou, Xinyang Hu, et al.. (2022). LncRNA LINC00942 promotes chemoresistance in gastric cancer by suppressing MSI2 degradation to enhance c‐Myc mRNA stability. Clinical and Translational Medicine. 12(1). e703–e703. 87 indexed citations
6.
Yan, Tao, Zongming Song, Shilong Ying, et al.. (2021). MD2 blockade prevents modified LDL-induced retinal injury in diabetes by suppressing NADPH oxidase-4 interaction with Toll-like receptor-4. Experimental & Molecular Medicine. 53(4). 681–694. 11 indexed citations
7.
Ying, Shilong, et al.. (2021). Linking the YTH domain to cancer: the importance of YTH family proteins in epigenetics. Cell Death and Disease. 12(4). 346–346. 63 indexed citations
8.
Zhu, Heping, Shilong Ying, Bingluo Zhou, et al.. (2020). Discovery of novel 2-aryl-3-sulfonamido-pyridines (HoAns) as microtubule polymerization inhibitors with potent antitumor activities. European Journal of Medicinal Chemistry. 211. 113117–113117. 8 indexed citations
9.
Yang, Lixian, Shilong Ying, Muchun Li, et al.. (2019). EGFR TKIs impair lysosome-dependent degradation of SQSTM1 to compromise the effectiveness in lung cancer. Signal Transduction and Targeted Therapy. 4(1). 25–25. 24 indexed citations
10.
Zhang, Yali, Beibei Wu, Hailing Zhang, et al.. (2017). Inhibition of MD2‐dependent inflammation attenuates the progression of non‐alcoholic fatty liver disease. Journal of Cellular and Molecular Medicine. 22(2). 936–947. 23 indexed citations
11.
Chen, Feng, Yiqun Xia, Peng Zou, et al.. (2017). Curcumin analog L48H37 induces apoptosis through ROS‐mediated endoplasmic reticulum stress and STAT3 pathways in human lung cancer cells. Molecular Carcinogenesis. 56(7). 1765–1777. 45 indexed citations
12.
Song, Zongming, Shilong Ying, Xi Yang, et al.. (2017). Myeloid differentiation protein 2 induced retinal ischemia reperfusion injury via upregulation of ROS through a TLR4-NOX4 pathway. Toxicology Letters. 282. 109–120. 16 indexed citations
13.
Zhang, Yali, Jianzhang Wu, Shilong Ying, et al.. (2016). Discovery of new MD2 inhibitor from chalcone derivatives with anti-inflammatory effects in LPS-induced acute lung injury. Scientific Reports. 6(1). 25130–25130. 51 indexed citations
14.
Ying, Shilong, Xiaojing Du, Weitao Fu, et al.. (2016). Synthesis, biological evaluation, QSAR and molecular dynamics simulation studies of potential fibroblast growth factor receptor 1 inhibitors for the treatment of gastric cancer. European Journal of Medicinal Chemistry. 127. 885–899. 19 indexed citations
15.
Chen, Weiqian, Peng Zou, Zhongwei Zhao, et al.. (2016). Selective killing of gastric cancer cells by a small molecule via targeting TrxR1 and ROS-mediated ER stress activation. Oncotarget. 7(13). 16593–16609. 49 indexed citations
16.
Xia, Yiqun, Zhankun Wang, Guanqun Huang, et al.. (2015). W346 inhibits cell growth, invasion, induces cycle arrest and potentiates apoptosis in human gastric cancer cells in vitro through the NF-κB signaling pathway. Tumor Biology. 37(4). 4791–4801. 16 indexed citations
17.
Fan, Lei, Wulan Li, Shilong Ying, et al.. (2015). A peptide derivative serves as a fibroblast growth factor 2 antagonist in human gastric cancer. Tumor Biology. 36(9). 7233–7241. 6 indexed citations
18.
Li, Wulan, Xiaojing Du, Qiuxiang Chen, et al.. (2015). Peptidomimetic suppresses proliferation and invasion of gastric cancer cells by fibroblast growth factor 2 signaling cascade blockage. Anti-Cancer Drugs. 27(3). 164–172. 4 indexed citations
19.
Zou, Peng, Minxiao Chen, Jiansong Ji, et al.. (2015). Auranofin induces apoptosis by ROS-mediated ER stress and mitochondrial dysfunction and displayed synergistic lethality with piperlongumine in gastric cancer. Oncotarget. 6(34). 36505–36521. 116 indexed citations
20.
Fan, Lei, Hang Xie, Hui Ye, et al.. (2014). A novel FGF2 antagonist peptide P8 with potent antiproliferation activity. Tumor Biology. 35(10). 10571–10579. 9 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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