Shi Hu

2.7k total citations · 1 hit paper
53 papers, 1.7k citations indexed

About

Shi Hu is a scholar working on Oncology, Molecular Biology and Immunology. According to data from OpenAlex, Shi Hu has authored 53 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Oncology, 19 papers in Molecular Biology and 19 papers in Immunology. Recurrent topics in Shi Hu's work include Monoclonal and Polyclonal Antibodies Research (16 papers), HER2/EGFR in Cancer Research (7 papers) and CAR-T cell therapy research (7 papers). Shi Hu is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (16 papers), HER2/EGFR in Cancer Research (7 papers) and CAR-T cell therapy research (7 papers). Shi Hu collaborates with scholars based in China, United States and Japan. Shi Hu's co-authors include Wenyan Fu, Changhai Lei, Kewen Qian, Min Ding, Li Tian, Sheng Zhang, Fangxing Lin, Yafeng Shen, Yongji Yang and Xuting Ye and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Shi Hu

51 papers receiving 1.7k citations

Hit Papers

CAR exosomes derived from... 2019 2026 2021 2023 2019 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. CAR exosomes derived from effector CAR-T cells have potent antitumour effects and low toxicity
    2019 389 citations Wenyan Fu, Changhai Lei et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shi Hu China 20 832 474 441 338 338 53 1.7k
Samir Parekh United States 29 1.3k 1.5× 1.3k 2.7× 512 1.2× 179 0.5× 157 0.5× 179 2.8k
Bo Chen China 23 875 1.1× 758 1.6× 251 0.6× 155 0.5× 223 0.7× 114 1.9k
Nakhle S. Saba United States 17 634 0.8× 361 0.8× 291 0.7× 80 0.2× 159 0.5× 65 1.6k
Bruce Freimark United States 17 997 1.2× 458 1.0× 785 1.8× 183 0.5× 98 0.3× 43 2.1k
Changhua Ji United States 24 883 1.1× 495 1.0× 281 0.6× 189 0.6× 189 0.6× 57 1.7k
Annkristin Heine Germany 26 1.0k 1.3× 662 1.4× 847 1.9× 109 0.3× 208 0.6× 66 2.4k
Nikoletta Lendvai United States 26 915 1.1× 839 1.8× 327 0.7× 326 1.0× 314 0.9× 111 2.0k
Giulia Maria Stella Italy 23 564 0.7× 540 1.1× 317 0.7× 193 0.6× 176 0.5× 111 2.1k
Alain Piché Canada 27 994 1.2× 680 1.4× 556 1.3× 102 0.3× 112 0.3× 57 1.9k

Countries citing papers authored by Shi Hu

Since Specialization
Citations

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

Fields of papers citing papers by Shi Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shi Hu

This figure shows the co-authorship network connecting the top 25 collaborators of Shi Hu. A scholar is included among the top collaborators of Shi Hu 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 Shi Hu. Shi Hu 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.
Deng, Rui, Duo Sun, Wei Ye, et al.. (2025). Intelligent microscopic imaging system based on microwell array chip for high-throughput analysis of single-cell heterogeneity. Microchemical Journal. 211. 113136–113136. 1 indexed citations
2.
3.
Wang, Tiantian, et al.. (2025). Research progress of antibody coupling technique in targeted drug delivery. SHILAP Revista de lepidopterología. 3(3).
4.
Qian, Kewen, Guangyao Li, Shuyi Zhang, et al.. (2024). Small extracellular vesicles purification and scale-up. Frontiers in Immunology. 15. 1344681–1344681. 19 indexed citations
5.
Zhang, Shuyi, Guangyao Li, Kewen Qian, et al.. (2024). Exosomes derived from cancer cells relieve inflammatory bowel disease in mice. Journal of drug targeting. 32(9). 1073–1085. 1 indexed citations
6.
Qian, Kewen, Guangyao Li, Shuyi Zhang, et al.. (2024). The application of antibody-based agents in cancer therapy based on their mechanisms of action. Fundamental Research. 5(5). 2343–2360. 3 indexed citations
7.
Li, Guangyao, et al.. (2024). Exosomes of immune cell origin and their therapeutic potential for tumors. SHILAP Revista de lepidopterología. 5(5). 18 indexed citations
8.
Gou, Shuangquan, Adriana C. Panayi, Rong Wang, et al.. (2023). Bioresponsive Self‐Reinforcing Sericin/Silk Fibroin Hydrogel for Relieving the Immune‐Related Adverse Events in Tumor Immunotherapy. Advanced Functional Materials. 33(15). 26 indexed citations
9.
Shen, Xian, Wenyan Fu, Yongpeng Wei, et al.. (2021). TIGIT-Fc Promotes Antitumor Immunity. Cancer Immunology Research. 9(9). 1088–1097. 10 indexed citations
10.
Fu, Wenyan, et al.. (2021). TIGIT-Fc as a Potential Therapeutic Agent for Fetomaternal Tolerance. Frontiers in Immunology. 12. 649135–649135. 10 indexed citations
11.
Qian, Kewen & Shi Hu. (2020). Ig-like ACE2 protein therapeutics: A revival in development during the COVID-19 pandemic. mAbs. 12(1). e1782600–e1782600. 5 indexed citations
12.
Hu, Shi, et al.. (2020). Simple and Accurate Uncertainty Quantification from Bias-Variance Decomposition. arXiv (Cornell University). 1 indexed citations
13.
Fu, Wenyan, Changhai Lei, Yue Yu, et al.. (2019). EGFR/Notch Antagonists Enhance the Response to Inhibitors of the PI3K-Akt Pathway by Decreasing Tumor-Initiating Cell Frequency. Clinical Cancer Research. 25(9). 2835–2847. 29 indexed citations
14.
Hu, Shi, et al.. (2019). Development and Validation of Nomograms for Predicting the Prognosis of Triple-Negative Breast Cancer Patients Based on 379 Chinese Patients. SHILAP Revista de lepidopterología. 1 indexed citations
15.
Jiang, Yu, Shi Hu, Liang Ren, et al.. (2019). Association Between Glucose Metabolism And Vascular Aging In Chinese Adults: A Cross-Sectional Analysis In The Tianning Cohort Study. SHILAP Revista de lepidopterología. 1 indexed citations
16.
17.
Yu, Xiaojie, Lingfei Wang, Yafeng Shen, et al.. (2017). Targeting EGFR/HER2 heterodimerization with a novel anti-HER2 domain II/III antibody. Molecular Immunology. 87. 300–307. 19 indexed citations
18.
19.
Liang, Shuaiyi, Jianxin Dai, Sheng Hou, et al.. (2013). Structural Basis for Treating Tumor Necrosis Factor α (TNFα)-associated Diseases with the Therapeutic Antibody Infliximab. Journal of Biological Chemistry. 288(19). 13799–13807. 85 indexed citations
20.
Li, Bohua, Yanchun Meng, Lei Zheng, et al.. (2013). Bispecific Antibody to ErbB2 Overcomes Trastuzumab Resistance through Comprehensive Blockade of ErbB2 Heterodimerization. Cancer Research. 73(21). 6471–6483. 47 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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