Shubiao Zhang

8.9k total citations · 3 hit papers
113 papers, 6.6k citations indexed

About

Shubiao Zhang is a scholar working on Molecular Biology, Biomaterials and Genetics. According to data from OpenAlex, Shubiao Zhang has authored 113 papers receiving a total of 6.6k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Molecular Biology, 25 papers in Biomaterials and 23 papers in Genetics. Recurrent topics in Shubiao Zhang's work include RNA Interference and Gene Delivery (56 papers), Advanced biosensing and bioanalysis techniques (40 papers) and Virus-based gene therapy research (21 papers). Shubiao Zhang is often cited by papers focused on RNA Interference and Gene Delivery (56 papers), Advanced biosensing and bioanalysis techniques (40 papers) and Virus-based gene therapy research (21 papers). Shubiao Zhang collaborates with scholars based in China, Ethiopia and Australia. Shubiao Zhang's co-authors include Shaohui Cui, Bing Wang, Hongtao Lv, Jie Yan, Defu Zhi, Ting Yang, Yinan Zhao, Budiao Zhao, Yinan Zhao and Huiming Jiang and has published in prestigious journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and ACS Nano.

In The Last Decade

Shubiao Zhang

109 papers receiving 6.6k citations

Hit Papers

Toxicity of cationic lipids and cationic polymers in gene... 2006 2026 2012 2019 2006 2020 2021 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shubiao Zhang China 34 4.5k 1.6k 1.4k 1.1k 627 113 6.6k
Inge S. Zuhorn Netherlands 34 4.5k 1.0× 1.6k 1.0× 1.7k 1.2× 850 0.8× 918 1.5× 65 6.9k
Gaurav Sahay United States 37 5.7k 1.3× 1.8k 1.1× 2.1k 1.5× 784 0.7× 639 1.0× 69 8.4k
Tuo Wei China 32 4.6k 1.0× 1.9k 1.1× 1.8k 1.3× 774 0.7× 758 1.2× 68 7.1k
Hu‐Lin Jiang China 46 3.0k 0.7× 2.2k 1.4× 1.8k 1.2× 755 0.7× 796 1.3× 195 6.7k
Shigeru Kawakami Japan 50 4.7k 1.0× 1.3k 0.8× 1.4k 1.0× 1.1k 1.1× 505 0.8× 221 6.9k
Qiang Cheng China 37 5.4k 1.2× 1.2k 0.7× 1.2k 0.8× 973 0.9× 388 0.6× 86 6.9k
Sérgio Simões Portugal 48 4.4k 1.0× 1.5k 0.9× 1.7k 1.2× 1.0k 1.0× 765 1.2× 152 7.3k
Chantal Pichon France 47 4.5k 1.0× 1.2k 0.7× 875 0.6× 1.3k 1.2× 661 1.1× 196 7.1k
Kenneth A. Howard Denmark 42 4.3k 1.0× 1.5k 0.9× 1.6k 1.1× 578 0.5× 652 1.0× 108 6.8k
Ji Hoon Jeong South Korea 55 4.7k 1.0× 2.2k 1.3× 2.2k 1.5× 978 0.9× 1.2k 1.8× 183 9.0k

Countries citing papers authored by Shubiao Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Shubiao Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shubiao Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Shubiao Zhang. A scholar is included among the top collaborators of Shubiao 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 Shubiao Zhang. Shubiao 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.
Chen, Huiying, et al.. (2025). Imidazolyl crosslinked chitosan nanogel for nanoconfined synthesis of silver nanocrystallines as antimicrobials. International Journal of Biological Macromolecules. 305(Pt 2). 140838–140838. 1 indexed citations
2.
Yang, Xuan, Zhou Su, Yinan Zhao, et al.. (2025). Lipoic Acid Capped Ag2S Quantum Dots for Mitochondria-Targeted NIR-II Fluorescence/Photoacoustic Imaging and Chemotherapy/Photothermal Treatment of Tumors. ACS Applied Nano Materials. 8(8). 3737–3748. 3 indexed citations
3.
Yang, Chao, Ze Liang, Kexin Zhang, et al.. (2025). Cyclic RGD modified dextran-quercetin polymer micelles for targeted therapy of breast cancer. International Journal of Biological Macromolecules. 308(Pt 1). 142272–142272. 3 indexed citations
4.
Yang, Xuan, et al.. (2024). Development of tumor marker detection and tumor treatment based on silver nanozymes. Sensors and Actuators B Chemical. 411. 135692–135692. 3 indexed citations
5.
Gao, Xiuhua, Hong‐Wei Sun, Yandong Liu, et al.. (2024). MdILL6 regulates xylem and vessel development to control internode elongation in spur‐type apple. Physiologia Plantarum. 176(6). e14613–e14613.
6.
Muhammad, Turghun, et al.. (2024). Batch adsorption kinetic and thermodynamic studies of flavonoids from Dracocephalum Moldavia via flow injection online measurement. Separation and Purification Technology. 351. 128033–128033. 8 indexed citations
7.
Fu, Xingxing, et al.. (2024). Application of machine learning for high-throughput tumor marker screening. Life Sciences. 348. 122634–122634. 6 indexed citations
8.
Sun, Jiao, Min Li, Zhe Wang, et al.. (2023). Delivery of quercetin for breast cancer and targeting potentiation via hyaluronic nano-micelles. International Journal of Biological Macromolecules. 242(Pt 2). 124736–124736. 38 indexed citations
12.
Li, Min, Yinan Zhao, Jiao Sun, et al.. (2022). pH/reduction dual-responsive hyaluronic acid-podophyllotoxin prodrug micelles for tumor targeted delivery. Carbohydrate Polymers. 288. 119402–119402. 51 indexed citations
13.
Zhi, Defu, et al.. (2019). Targeting strategies for superparamagnetic iron oxide nanoparticles in cancer therapy. Acta Biomaterialia. 102. 13–34. 204 indexed citations
14.
Gao, Qinqin, Chuanmin Zhang, En Xia Zhang, et al.. (2019). Zwitterionic pH-responsive hyaluronic acid polymer micelles for delivery of doxorubicin. Colloids and Surfaces B Biointerfaces. 178. 412–420. 42 indexed citations
15.
Zhang, Chuanmin, Shubiao Zhang, Defu Zhi, & Jingnan Cui. (2018). Cancer Treatment with Liposomes Based Drugs and Genes Co-delivery Systems. Current Medicinal Chemistry. 25(28). 3319–3332. 13 indexed citations
16.
Chen, Huiying, Yu Ma, Yinan Zhao, et al.. (2018). Dual stimuli-responsive saccharide core based nanocarrier for efficient Birc5-shRNA delivery. Journal of Materials Chemistry B. 6(45). 7530–7542. 7 indexed citations
17.
Fu, Shuang, Xiaodong Xu, Yu Ma, Shubiao Zhang, & Shufen Zhang. (2018). RGD peptide-based non-viral gene delivery vectors targeting integrin α v β 3 for cancer therapy. Journal of drug targeting. 27(1). 1–11. 101 indexed citations
18.
Zhao, Yinan, Jie Zhu, Hengjun Zhou, et al.. (2016). Sucrose ester based cationic liposomes as effective non-viral gene vectors for gene delivery. Colloids and Surfaces B Biointerfaces. 145. 454–461. 19 indexed citations
19.
Zhang, Shubiao, Yinan Zhao, Defu Zhi, & Shufen Zhang. (2011). Non-viral vectors for the mediation of RNAi. Bioorganic Chemistry. 40(1). 10–18. 29 indexed citations
20.
Jiang, Huiming, et al.. (2007). New crystal structure of molecular complex 1-piperidine carboxylate-piperidinium-H2O studied by X-ray single crystal diffraction. Wuhan University Journal of Natural Sciences. 12(6). 1099–1104. 4 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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