Jiang‐Sha Zhao

1.8k total citations · 1 hit paper
18 papers, 1.4k citations indexed

About

Jiang‐Sha Zhao is a scholar working on Molecular Biology, Cell Biology and Oncology. According to data from OpenAlex, Jiang‐Sha Zhao has authored 18 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 7 papers in Cell Biology and 5 papers in Oncology. Recurrent topics in Jiang‐Sha Zhao's work include Hippo pathway signaling and YAP/TAZ (4 papers), Hepatocellular Carcinoma Treatment and Prognosis (3 papers) and Liver physiology and pathology (3 papers). Jiang‐Sha Zhao is often cited by papers focused on Hippo pathway signaling and YAP/TAZ (4 papers), Hepatocellular Carcinoma Treatment and Prognosis (3 papers) and Liver physiology and pathology (3 papers). Jiang‐Sha Zhao collaborates with scholars based in China, United States and Singapore. Jiang‐Sha Zhao's co-authors include Dong Xie, Yuezhen Deng, Yuxiong Feng, Steven X. Hou, Shanglei Ning, Yun Zhang, Geoffrey J. Markowitz, Shan Jiang, Yunfei Yuan and Pengyuan Yang and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Jiang‐Sha Zhao

18 papers receiving 1.4k citations

Hit Papers

TGF-β-miR-34a-CCL22 Signaling-Induced Treg Cell Recruitme... 2012 2026 2016 2021 2012 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jiang‐Sha Zhao China 13 871 520 386 267 157 18 1.4k
Yuezhen Deng China 20 1.1k 1.3× 646 1.2× 421 1.1× 330 1.2× 189 1.2× 34 1.8k
Claudio Raimondi United Kingdom 18 841 1.0× 234 0.5× 233 0.6× 106 0.4× 62 0.4× 27 1.2k
Wan-Chi Lin United States 9 642 0.7× 466 0.9× 747 1.9× 166 0.6× 221 1.4× 12 1.4k
Martina Welzel Germany 16 735 0.8× 212 0.4× 578 1.5× 505 1.9× 133 0.8× 20 1.3k
Huahong Xie China 22 812 0.9× 441 0.8× 249 0.6× 69 0.3× 98 0.6× 43 1.1k
Abbas Fotovati Canada 24 1.2k 1.3× 320 0.6× 529 1.4× 247 0.9× 82 0.5× 35 1.7k
Rachel Gredler United States 21 805 0.9× 292 0.6× 474 1.2× 166 0.6× 51 0.3× 24 1.3k
Ewa Stępniak-Konieczna Poland 13 1.0k 1.2× 162 0.3× 224 0.6× 70 0.3× 124 0.8× 16 1.3k
Fei-Meng Zheng China 20 1.1k 1.3× 538 1.0× 484 1.3× 94 0.4× 121 0.8× 33 1.7k
Ning‐Fang Ma China 14 1.1k 1.3× 622 1.2× 325 0.8× 135 0.5× 92 0.6× 29 1.5k

Countries citing papers authored by Jiang‐Sha Zhao

Since Specialization
Citations

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

Fields of papers citing papers by Jiang‐Sha Zhao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jiang‐Sha Zhao. 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 Jiang‐Sha Zhao. The network helps show where Jiang‐Sha Zhao may publish in the future.

Co-authorship network of co-authors of Jiang‐Sha Zhao

This figure shows the co-authorship network connecting the top 25 collaborators of Jiang‐Sha Zhao. A scholar is included among the top collaborators of Jiang‐Sha Zhao 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 Jiang‐Sha Zhao. Jiang‐Sha Zhao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Yang, Lixian, Lu Si, Jiang‐Sha Zhao, et al.. (2025). Alleviation of liver fibrosis by inhibiting a non-canonical ATF4-regulated enhancer program in hepatic stellate cells. Nature Communications. 16(1). 524–524. 9 indexed citations
2.
Chen, Liangen, et al.. (2024). Linking fatty liver diseases to hepatocellular carcinoma by hepatic stellate cells. SHILAP Revista de lepidopterología. 4(1). 25–35. 4 indexed citations
3.
Zhao, Jiang‐Sha, Jing Yang, Zhimin Lu, & Yuxiong Feng. (2023). Licensing instead of fueling: Glutamine synthetase promotes mitotic progression via a non-metabolic mechanism. SHILAP Revista de lepidopterología. 4. 3–3. 1 indexed citations
4.
Si, Lu, et al.. (2021). Transcriptional Control of Metastasis by Integrated Stress Response Signaling. Frontiers in Oncology. 11. 770843–770843. 6 indexed citations
5.
Wang, Guohao, Junji Xu, Jiang‐Sha Zhao, et al.. (2020). Arf1-mediated lipid metabolism sustains cancer cells and its ablation induces anti-tumor immune responses in mice. Nature Communications. 11(1). 220–220. 88 indexed citations
6.
Li, Jingjing, Hongkun Yin, Dongxian Guan, et al.. (2018). Chemerin suppresses hepatocellular carcinoma metastasis through CMKLR1-PTEN-Akt axis. British Journal of Cancer. 118(10). 1337–1348. 58 indexed citations
7.
Zhao, Jiang‐Sha, et al.. (2017). Glycolytic reprogramming through PCK2 regulates tumor initiation of prostate cancer cells. Oncotarget. 8(48). 83602–83618. 46 indexed citations
8.
Singh, Shree Ram, Ying Liu, Jiang‐Sha Zhao, Xiankun Zeng, & Steven X. Hou. (2016). The novel tumour suppressor Madm regulates stem cell competition in the Drosophila testis. Nature Communications. 7(1). 10473–10473. 25 indexed citations
9.
Singh, Shree Ram, Xiankun Zeng, Jiang‐Sha Zhao, et al.. (2016). The lipolysis pathway sustains normal and transformed stem cells in adult Drosophila. Nature. 538(7623). 109–113. 72 indexed citations
10.
Liu, Ying, Shree Ram Singh, Xiankun Zeng, Jiang‐Sha Zhao, & Steven X. Hou. (2015). The Nuclear Matrix Protein Megator Regulates Stem Cell Asymmetric Division through the Mitotic Checkpoint Complex in Drosophila Testes. PLoS Genetics. 11(12). e1005750–e1005750. 9 indexed citations
11.
12.
Zhang, Yang, Dongxian Guan, Jie Shi, et al.. (2013). All-trans retinoic acid potentiates the chemotherapeutic effect of cisplatin by inducing differentiation of tumor initiating cells in liver cancer. Journal of Hepatology. 59(6). 1255–1263. 78 indexed citations
13.
Shi, Shuo, Yuezhen Deng, Jiang‐Sha Zhao, et al.. (2012). RACK1 Promotes Non-small-cell Lung Cancer Tumorigenicity through Activating Sonic Hedgehog Signaling Pathway. Journal of Biological Chemistry. 287(11). 7845–7858. 76 indexed citations
14.
Guo, Li, Xiao‐Dan Ji, Hong Gao, et al.. (2012). EphB3 suppresses non-small-cell lung cancer metastasis via a PP2A/RACK1/Akt signalling complex. Nature Communications. 3(1). 667–667. 101 indexed citations
15.
Yang, Pengyuan, Qi-Jing Li, Yuxiong Feng, et al.. (2012). TGF-β-miR-34a-CCL22 Signaling-Induced Treg Cell Recruitment Promotes Venous Metastases of HBV-Positive Hepatocellular Carcinoma. Cancer Cell. 22(3). 291–303. 456 indexed citations breakdown →
16.
Ji, Xiao‐Dan, Li Guo, Yuxiong Feng, et al.. (2011). EphB3 Is Overexpressed in Non–Small-Cell Lung Cancer and Promotes Tumor Metastasis by Enhancing Cell Survival and Migration. Cancer Research. 71(3). 1156–1166. 87 indexed citations
17.
Liu, Shupeng, Wei‐Xing Guo, Jie Shi, et al.. (2011). MicroRNA-135a contributes to the development of portal vein tumor thrombus by promoting metastasis in hepatocellular carcinoma. Journal of Hepatology. 56(2). 389–396. 132 indexed citations
18.
Zhao, Jiang‐Sha, Wenjie Li, Di Ge, et al.. (2011). Tumor Initiating Cells in Esophageal Squamous Cell Carcinomas Express High Levels of CD44. PLoS ONE. 6(6). e21419–e21419. 92 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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