Liu Shui

968 total citations · 1 hit paper
8 papers, 669 citations indexed

About

Liu Shui is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Biomaterials. According to data from OpenAlex, Liu Shui has authored 8 papers receiving a total of 669 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 2 papers in Cellular and Molecular Neuroscience and 2 papers in Biomaterials. Recurrent topics in Liu Shui's work include Viral Infectious Diseases and Gene Expression in Insects (2 papers), Electrospun Nanofibers in Biomedical Applications (2 papers) and Radiomics and Machine Learning in Medical Imaging (1 paper). Liu Shui is often cited by papers focused on Viral Infectious Diseases and Gene Expression in Insects (2 papers), Electrospun Nanofibers in Biomedical Applications (2 papers) and Radiomics and Machine Learning in Medical Imaging (1 paper). Liu Shui collaborates with scholars based in China, Netherlands and United Kingdom. Liu Shui's co-authors include Jiyao Sheng, Xuewen Zhang, Ranji Cui, Yicun Wang, Hanjiao Qin, Bingjin Li, Chao Lin, Mengying Cui, Songmei Wang and Xiaodi Niu and has published in prestigious journals such as Blood, Radiology and Frontiers in Microbiology.

In The Last Decade

Liu Shui

8 papers receiving 660 citations

Hit Papers

The Link between Depression and Chronic Pain: Neural Mech... 2017 2026 2020 2023 2017 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Liu Shui China 5 207 153 153 109 97 8 669
Lisa Doan United States 14 258 1.2× 61 0.4× 198 1.3× 114 1.0× 102 1.1× 39 699
Ümit Hıdır Ulaş Türkiye 18 117 0.6× 293 1.9× 187 1.2× 134 1.2× 91 0.9× 67 860
Andrew Clair United States 15 299 1.4× 314 2.1× 218 1.4× 153 1.4× 46 0.5× 35 698
Mark H. Pitcher United States 13 285 1.4× 107 0.7× 386 2.5× 134 1.2× 199 2.1× 24 858
Masako Iseki Japan 14 129 0.6× 61 0.4× 236 1.5× 63 0.6× 71 0.7× 68 572
Xueyong Shen China 20 406 2.0× 115 0.8× 344 2.2× 171 1.6× 56 0.6× 113 1.4k
Seoyon Yang South Korea 15 224 1.1× 110 0.7× 279 1.8× 76 0.7× 63 0.6× 49 929
Michael Bernateck Germany 14 212 1.0× 184 1.2× 153 1.0× 105 1.0× 65 0.7× 41 697
Isabelle Gaumond Canada 12 299 1.4× 212 1.4× 412 2.7× 174 1.6× 122 1.3× 21 744
Olivia Hogue United States 14 142 0.7× 192 1.3× 73 0.5× 173 1.6× 144 1.5× 64 735

Countries citing papers authored by Liu Shui

Since Specialization
Citations

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

Fields of papers citing papers by Liu Shui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liu Shui

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

All Works

8 of 8 papers shown
1.
Zheng, Sunyi, Jing Wang, Dongsheng Yue, et al.. (2025). Comparison of a Specialized Large Language Model with GPT-4o for CT and MRI Radiology Report Summarization. Radiology. 316(2). e243774–e243774. 1 indexed citations
2.
Liu, Weiping, Bo Jiang, Ying Tan, et al.. (2023). Safety and Efficacy of a-319 (a CD3xCD19 T cell engager) in Patients with Relapsed or Refractory B-Cell Non-Hodgkin Lymphoma. Blood. 142(Supplement 1). 6158–6158. 2 indexed citations
3.
Lin, Chao, et al.. (2020). Long non-coding RNA CRNDE promotes malignant progression of hepatocellular carcinoma through the miR-33a-5p/CDK6 axis. Journal of Physiology and Biochemistry. 76(3). 469–481. 21 indexed citations
4.
Wang, Jianfeng, Liu Shui, Bowen Liu, Xiaodi Niu, & Xuming Deng. (2019). Luteolin Inhibits Listeriolysin O Translation by Directly Targeting the Coding Region of the hly mRNA. Frontiers in Microbiology. 10. 1496–1496. 10 indexed citations
5.
Sheng, Jiyao, Liu Shui, Yicun Wang, Ranji Cui, & Xuewen Zhang. (2017). The Link between Depression and Chronic Pain: Neural Mechanisms in the Brain. Neural Plasticity. 2017. 1–10. 516 indexed citations breakdown →
6.
Sheng, Jiyao, Liu Shui, Hanjiao Qin, Bingjin Li, & Xuewen Zhang. (2017). Drug-Resistant Epilepsy and Surgery. Current Neuropharmacology. 16(1). 17–28. 98 indexed citations
7.
Shui, Liu. (2010). BIOCOMPATIBILITY OF PHBHHx AND SILK FIBROIN-MODIFIED PHBHHx SCAFFOLDS WITH HUMAN UMBILICAL VEIN ENDOTHELIAL CELLS. Acta Polymerica Sinica. 2 indexed citations
8.
Shui, Liu, Ping Zhou, Yi Zhang, et al.. (2008). Differentiation of smooth muscle progenitor cells in peripheral blood and its application in tissue engineered blood vessels. Journal of Zhejiang University SCIENCE B. 9(12). 923–930. 19 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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