Shu Zhang

15.1k total citations · 4 hit papers
351 papers, 9.6k citations indexed

About

Shu Zhang is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Shu Zhang has authored 351 papers receiving a total of 9.6k indexed citations (citations by other indexed papers that have themselves been cited), including 149 papers in Molecular Biology, 82 papers in Oncology and 57 papers in Cancer Research. Recurrent topics in Shu Zhang's work include MicroRNA in disease regulation (26 papers), Liver Disease Diagnosis and Treatment (26 papers) and Glycosylation and Glycoproteins Research (22 papers). Shu Zhang is often cited by papers focused on MicroRNA in disease regulation (26 papers), Liver Disease Diagnosis and Treatment (26 papers) and Glycosylation and Glycoproteins Research (22 papers). Shu Zhang collaborates with scholars based in China, United States and United Kingdom. Shu Zhang's co-authors include Ted Weita Lai, Yu Tian Wang, Yinkun Liu, Lian‐Shun Feng, Qiang Gao, Jia Fan, Zongfang Li, Jun Yang, Zhi Xu and Le Chang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Oncology.

In The Last Decade

Shu Zhang

335 papers receiving 9.4k citations

Hit Papers

Excitotoxicity and stroke: Identifying novel targets for ... 2013 2026 2017 2021 2013 2017 2022 2024 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shu Zhang China 47 4.6k 1.9k 1.8k 1.3k 1.2k 351 9.6k
Shrikant Anant United States 56 5.3k 1.2× 2.2k 1.2× 1.5k 0.8× 1.5k 1.2× 742 0.6× 212 9.3k
Li Li China 48 4.7k 1.0× 2.1k 1.1× 1.4k 0.8× 1.2k 1.0× 1.2k 1.0× 420 9.9k
Shazib Pervaiz Singapore 58 5.9k 1.3× 1.3k 0.7× 1.5k 0.8× 1.0k 0.8× 1.0k 0.8× 176 9.9k
Amir Avan Iran 50 4.6k 1.0× 1.9k 1.0× 2.4k 1.3× 798 0.6× 875 0.7× 344 9.1k
Lorne J. Hofseth United States 48 3.9k 0.9× 2.2k 1.2× 1.7k 0.9× 1.3k 1.0× 675 0.6× 97 8.7k
Ling Li China 45 3.7k 0.8× 1.1k 0.6× 1.1k 0.6× 1.0k 0.8× 951 0.8× 304 7.0k
Lucia Altucci Italy 62 9.9k 2.2× 2.1k 1.1× 1.5k 0.8× 1.1k 0.9× 1.0k 0.9× 321 14.5k
Canhua Huang China 66 7.3k 1.6× 2.2k 1.2× 2.8k 1.6× 2.2k 1.8× 1.8k 1.5× 225 13.7k
Jun O. Liu United States 64 8.9k 2.0× 2.7k 1.5× 1.7k 0.9× 1.5k 1.2× 1.4k 1.2× 210 14.2k
Qiaojun He China 59 6.4k 1.4× 2.5k 1.4× 1.8k 1.0× 1.7k 1.3× 942 0.8× 415 12.0k

Countries citing papers authored by Shu Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Shu Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shu Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Shu Zhang. A scholar is included among the top collaborators of Shu 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 Shu Zhang. Shu 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
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3.
Kang, Yue, et al.. (2024). A review of bioinformatics analysis and its digestibility of Sorghum bicolor Kafirins. Journal of Food Composition and Analysis. 134. 106595–106595. 1 indexed citations
4.
Gao, Ke, Yin Li, Yingcheng Wu, et al.. (2024). ST3GAL1 Promotes Malignant Phenotypes in Intrahepatic Cholangiocarcinoma. Molecular & Cellular Proteomics. 23(9). 100821–100821. 4 indexed citations
5.
Xiong, Yongqiang, et al.. (2024). Shorter telomere length increases the risk of lymphocyte immunodeficiency: A Mendelian randomization study. Immunity Inflammation and Disease. 12(4). e1251–e1251. 5 indexed citations
7.
Gao, Yuan, Zhuxin Zhang, Mengxing Cai, et al.. (2024). The triglyceride-glucose index, ventricular arrhythmias and major cardiovascular events in patients at high risk of sudden cardiac death. Cardiovascular Diabetology. 23(1). 382–382. 5 indexed citations
8.
Liu, Song, Jiayao Yang, Yi Liu, et al.. (2023). Rhein Exhibits Anti-Inflammatory Effects in Chronic Atrophic Gastritis via Nrf2 and MAPK Signaling. The Turkish Journal of Gastroenterology. 34(5). 525–532. 17 indexed citations
9.
Anania, Gabriele, Alberto Arezzo, Richard Justin Davies, et al.. (2021). A global systematic review and meta-analysis on laparoscopic vs open right hemicolectomy with complete mesocolic excision. International Journal of Colorectal Disease. 36(8). 1609–1620. 15 indexed citations
10.
Jin, Qin, Yanfeng Dai, Yan Wang, Shu Zhang, & Gang Liu. (2019). High kinesin family member 11 expression predicts poor prognosis in patients with clear cell renal cell carcinoma. Journal of Clinical Pathology. 72(5). 354–362. 32 indexed citations
11.
Duan, Meng, Shyamal Goswami, Jie-Yi Shi, et al.. (2019). Activated and Exhausted MAIT Cells Foster Disease Progression and Indicate Poor Outcome in Hepatocellular Carcinoma. Clinical Cancer Research. 25(11). 3304–3316. 114 indexed citations
12.
Zhang, Shu, Qiang Wang, Xiaoxia Qiu, et al.. (2017). Achaete-scute complex homologue-1 promotes development of laryngocarcinoma via facilitating the epithelial–mesenchymal transformation. Tumor Biology. 39(6). 3726132175–3726132175. 7 indexed citations
13.
Zhou, Jinhua, Shu Zhang, Abdulkhaliq Alsaadi, et al.. (2016). A Novel Compound ARN-3236 Inhibits Salt-Inducible Kinase 2 and Sensitizes Ovarian Cancer Cell Lines and Xenografts to Paclitaxel. Clinical Cancer Research. 23(8). 1945–1954. 48 indexed citations
14.
Liu, Li, Patrick A. Mayes, Stephen D. Eastman, et al.. (2015). The BRAF and MEK Inhibitors Dabrafenib and Trametinib: Effects on Immune Function and in Combination with Immunomodulatory Antibodies Targeting PD-1, PD-L1, and CTLA-4. Clinical Cancer Research. 21(7). 1639–1651. 352 indexed citations
15.
Zhang, Shu, et al.. (2015). Flavonoid Glycosides of Polygonum capitatum Protect against Inflammation Associated with Helicobacter pylori Infection. PLoS ONE. 10(5). e0126584–e0126584. 27 indexed citations
16.
Zhang, Shu, Zhen Lü, Anna K. Unruh, et al.. (2014). Clinically Relevant microRNAs in Ovarian Cancer. Molecular Cancer Research. 13(3). 393–401. 70 indexed citations
17.
Zhang, Shu, Jiang Deng, Yang Gao, et al.. (2012). Ginsenoside Rb1 inhibits the carotid neointimal hyperplasia induced by balloon injury in rats via suppressing the phenotype modulation of vascular smooth muscle cells. European Journal of Pharmacology. 685(1-3). 126–132. 25 indexed citations
18.
Zhang, Shu, Kyounghyun Kim, Catherine Pfent, et al.. (2011). Aryl Hydrocarbon Receptor Agonists Induce MicroRNA-335 Expression and Inhibit Lung Metastasis of Estrogen Receptor Negative Breast Cancer Cells. Molecular Cancer Therapeutics. 11(1). 108–118. 86 indexed citations
19.
Zhang, Shu, et al.. (2007). Efficacy of c-erbB-2 antisense oligonucleotide transfection on uterine endometrial cancer HEC-1A cell lines.. PubMed. 28(4). 263–9. 2 indexed citations
20.
Zhang, Shu. (2003). Adaptation of Hybridoma Cells to Serum-free Low-protein Culture. Huadong Li-Gong Daxue xuebao. 1 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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