Ying E. Zhang

19.6k total citations · 7 hit papers
102 papers, 16.4k citations indexed

About

Ying E. Zhang is a scholar working on Molecular Biology, Cancer Research and Pathology and Forensic Medicine. According to data from OpenAlex, Ying E. Zhang has authored 102 papers receiving a total of 16.4k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Molecular Biology, 19 papers in Cancer Research and 13 papers in Pathology and Forensic Medicine. Recurrent topics in Ying E. Zhang's work include TGF-β signaling in diseases (48 papers), Cancer-related gene regulation (14 papers) and ATP Synthase and ATPases Research (13 papers). Ying E. Zhang is often cited by papers focused on TGF-β signaling in diseases (48 papers), Cancer-related gene regulation (14 papers) and ATP Synthase and ATPases Research (13 papers). Ying E. Zhang collaborates with scholars based in United States, China and Germany. Ying E. Zhang's co-authors include Rik Derynck, Xin‐Hua Feng, Rui-Yun Wu, Motozo Yamashita, Robert Fillingame, Xiangchun Wang, Thomas J. Musci, Ali Hemmati‐Brivanlou, Daniel J. Gehling and Chenbei Chang and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Ying E. Zhang

100 papers receiving 16.2k citations

Hit Papers

Smad-dependent and Smad-independent pathways in TGF-β fam... 1996 2026 2006 2016 2003 2008 1998 1996 1998 1000 2.0k 3.0k 4.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ying E. Zhang United States 51 12.5k 3.5k 2.4k 1.3k 1.3k 102 16.4k
Aristidis Moustakas Sweden 68 13.1k 1.0× 5.7k 1.6× 3.5k 1.5× 1.4k 1.1× 1.5k 1.1× 161 17.8k
Xin‐Hua Feng United States 69 13.3k 1.1× 3.7k 1.0× 2.4k 1.0× 1.3k 1.0× 1.0k 0.8× 187 17.5k
Xiao Yang China 67 10.1k 0.8× 2.2k 0.6× 3.0k 1.3× 744 0.6× 1.0k 0.8× 314 15.0k
Rosemary J. Akhurst United States 49 8.7k 0.7× 4.4k 1.3× 1.7k 0.7× 959 0.7× 1.2k 0.9× 96 12.4k
Qian Tao China 60 6.8k 0.5× 3.2k 0.9× 2.1k 0.9× 1.3k 1.0× 937 0.7× 297 11.0k
William P. Schiemann United States 59 6.8k 0.5× 3.5k 1.0× 2.4k 1.0× 721 0.5× 1.3k 1.0× 132 11.1k
Yoshiaki Ito Japan 74 12.5k 1.0× 4.8k 1.3× 3.0k 1.3× 944 0.7× 1.8k 1.3× 422 19.4k
Kenneth J. Hillan United States 36 9.0k 0.7× 4.2k 1.2× 3.0k 1.3× 688 0.5× 2.5k 1.9× 57 14.6k
Akiko Hata United States 51 9.9k 0.8× 1.8k 0.5× 3.8k 1.6× 902 0.7× 1.1k 0.9× 109 13.2k
Ye‐Guang Chen China 52 8.8k 0.7× 2.2k 0.6× 1.4k 0.6× 634 0.5× 877 0.7× 178 12.2k

Countries citing papers authored by Ying E. Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Ying E. Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ying E. Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Ying E. Zhang. A scholar is included among the top collaborators of Ying E. Zhang 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 Ying E. Zhang. Ying E. Zhang 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.
Stappenbeck, Frank, Liu-Ya Tang, Ying E. Zhang, et al.. (2022). Oxy210, a Semi-Synthetic Oxysterol, Exerts Anti-Inflammatory Effects in Macrophages via Inhibition of Toll-like Receptor (TLR) 4 and TLR2 Signaling and Modulation of Macrophage Polarization. International Journal of Molecular Sciences. 23(10). 5478–5478. 14 indexed citations
2.
Stuelten, Christina H., Nicolas Mélis, Yi Tang, et al.. (2022). Smurf2 Regulates Inflammation and Collagen Processing in Cutaneous Wound Healing through Transforming Growth Factor-β/Smad3 Signaling. American Journal Of Pathology. 192(12). 1699–1711. 5 indexed citations
3.
Shi, Changgui, Bin Sun, Huiqiao Wu, et al.. (2020). Dysfunction of Caveolae-Mediated Endocytic TβRI Degradation Results in Hypersensitivity of TGF-β/Smad Signaling in Osteogenesis Imperfecta. Journal of Bone and Mineral Research. 38(1). 103–118. 4 indexed citations
4.
Zhu, Kun Yan, Yi Tang, Xuan Xu, et al.. (2018). Non-proteolytic ubiquitin modification of PPARγ by Smurf1 protects the liver from steatosis. PLoS Biology. 16(12). e3000091–e3000091. 22 indexed citations
5.
6.
Tu, Eric, Cheryl Chia, Weiwei Chen, et al.. (2018). T Cell Receptor-Regulated TGF-β Type I Receptor Expression Determines T Cell Quiescence and Activation. Immunity. 48(4). 745–759.e6. 63 indexed citations
7.
Zhao, Xuelian, Atsushi Takai, Stéphanie Roessler, et al.. (2015). Integrative genomics identifies YY1AP1 as an oncogenic driver in EpCAM+ AFP+ hepatocellular carcinoma. Oncogene. 34(39). 5095–5104. 40 indexed citations
8.
Yang, Li, et al.. (2015). 12 cases of primary thyroid lymphoma in China. Journal of Endocrinological Investigation. 38(7). 739–744. 16 indexed citations
9.
Zhang, Ying E., et al.. (2014). Minimally invasive retroperitoneoscopic surgery for psoas abscess with thoracolumbar tuberculosis. Surgical Endoscopy. 29(8). 2451–2455. 11 indexed citations
10.
Orvedahl, Anthony, Rhea Sumpter, Guanghua Xiao, et al.. (2011). Image-based genome-wide siRNA screen identifies selective autophagy factors. Nature. 480(7375). 113–117. 385 indexed citations breakdown →
11.
Wang, Meina, et al.. (2010). Smad3 Prevents β-Catenin Degradation and Facilitates β-Catenin Nuclear Translocation in Chondrocytes. Journal of Biological Chemistry. 285(12). 8703–8710. 81 indexed citations
12.
Yang, Yu-an, et al.. (2009). Smad Ubiquitination Regulatory Factor 2 Promotes Metastasis of Breast Cancer Cells by Enhancing Migration and Invasiveness. Cancer Research. 69(3). 735–740. 64 indexed citations
13.
Yamashita, Motozo, et al.. (2008). TRAF6 Mediates Smad-Independent Activation of JNK and p38 by TGF-β. Molecular Cell. 31(6). 918–924. 476 indexed citations
14.
Millet, Caroline & Ying E. Zhang. (2007). Roles of Smad3 in TGF-β Signaling During Carcinogenesis. Critical Reviews in Eukaryotic Gene Expression. 17(4). 281–293. 83 indexed citations
15.
Boyer, Laurent, Laurent Turchi, Benoît Desnues, et al.. (2006). CNF1-induced Ubiquitylation and Proteasome Destruction of Activated RhoA Is Impaired in Smurf1−/−Cells. Molecular Biology of the Cell. 17(6). 2489–2497. 54 indexed citations
16.
Roelen, Bernard A.J., Ori S. Cohen, Malay K. Raychowdhury, et al.. (2003). Phosphorylation of threonine 276 in Smad4 is involved in transforming growth factor-β-induced nuclear accumulation. American Journal of Physiology-Cell Physiology. 285(4). C823–C830. 52 indexed citations
17.
Derynck, Rik & Ying E. Zhang. (2003). Smad-dependent and Smad-independent pathways in TGF-β family signalling. Nature. 425(6958). 577–584. 4493 indexed citations breakdown →
18.
19.
Zhang, Ying E., Xin‐Hua Feng, Rui-Yun Wu, & Rik Derynck. (1996). Receptor-associated Mad homologues synergize as effectors of the TGF-β response. Nature. 383(6596). 168–172. 760 indexed citations breakdown →
20.
Derynck, Rik & Ying E. Zhang. (1996). Intracellular signalling: The Mad way to do it. Current Biology. 6(10). 1226–1229. 142 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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