Yi Shi

4.4k total citations · 1 hit paper
136 papers, 2.8k citations indexed

About

Yi Shi is a scholar working on Molecular Biology, Cancer Research and Surgery. According to data from OpenAlex, Yi Shi has authored 136 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Molecular Biology, 27 papers in Cancer Research and 25 papers in Surgery. Recurrent topics in Yi Shi's work include Cancer-related molecular mechanisms research (11 papers), Cancer Genomics and Diagnostics (9 papers) and Genomics and Chromatin Dynamics (8 papers). Yi Shi is often cited by papers focused on Cancer-related molecular mechanisms research (11 papers), Cancer Genomics and Diagnostics (9 papers) and Genomics and Chromatin Dynamics (8 papers). Yi Shi collaborates with scholars based in China, United States and Canada. Yi Shi's co-authors include Ze‐Guang Han, Gregory E. Wilding, Guohui Lin, Khurshid A. Guru, Liang Li, Tao Huan, Qing Luo, Harianto Tjong, Hanjun Shin and Ke Gong and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Yi Shi

128 papers receiving 2.7k citations

Hit Papers

Essential roles of exosome and circRNA_101093 on ferropto... 2022 2026 2023 2024 2022 40 80 120
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. Essential roles of exosome and circRNA_101093 on ferroptosis desensitization in lung adenocarcinoma
    2022 132 citations Xiao Zhang, Yunhua Xu et al. Cancer Communications profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yi Shi China 29 1.3k 588 383 325 321 136 2.8k
Yue Li China 31 1.4k 1.0× 350 0.6× 538 1.4× 201 0.6× 139 0.4× 199 3.3k
Masahiro Nakao Japan 35 1.4k 1.1× 285 0.5× 184 0.5× 354 1.1× 188 0.6× 144 3.6k
Ying Zhou China 30 2.0k 1.5× 309 0.5× 513 1.3× 255 0.8× 507 1.6× 128 3.8k
Ann Chen Taiwan 39 2.2k 1.6× 427 0.7× 219 0.6× 315 1.0× 133 0.4× 135 4.3k
Ju Han Kim South Korea 32 1.6k 1.2× 362 0.6× 573 1.5× 494 1.5× 93 0.3× 244 4.0k
Juan Chen China 28 1.1k 0.8× 253 0.4× 323 0.8× 400 1.2× 157 0.5× 195 2.8k
Peng Wei United States 30 1.5k 1.2× 273 0.5× 405 1.1× 159 0.5× 115 0.4× 178 3.2k
Tao Chen China 28 970 0.7× 633 1.1× 291 0.8× 238 0.7× 77 0.2× 242 3.3k
Kun Liu China 25 1.3k 1.0× 401 0.7× 721 1.9× 360 1.1× 139 0.4× 237 3.0k
Eric A.G. Blomme United States 30 1.2k 0.9× 426 0.7× 266 0.7× 288 0.9× 95 0.3× 77 3.3k

Countries citing papers authored by Yi Shi

Since Specialization
Citations

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

Fields of papers citing papers by Yi Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yi Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Yi Shi. A scholar is included among the top collaborators of Yi Shi 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 Yi Shi. Yi Shi 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.
Jia, Yujie, Xiao Liang, Li Zhang, et al.. (2025). Machine learning-assisted microfluidic approach for broad-spectrum liposome size control. Journal of Pharmaceutical Analysis. 15(6). 101221–101221. 6 indexed citations
2.
Wang, Xiaoxue, Kejia Xu, Beilei Zeng, et al.. (2024). Novel EGFR inhibitors against resistant L858R/T790M/C797S mutant for intervention of non-small cell lung cancer. European Journal of Medicinal Chemistry. 277. 116711–116711. 17 indexed citations
3.
Su, Peipei, et al.. (2024). Gene doping detection in the era of genomics. Drug Testing and Analysis. 16(12). 1468–1478. 7 indexed citations
4.
Shi, Yi, et al.. (2024). Advances in integrating single-cell sequencing data to unravel the mechanism of ferroptosis in cancer. Briefings in Functional Genomics. 23(6). 713–725. 1 indexed citations
5.
Wei, Xiaoxi, Liangjie Liu, Lin Lin, et al.. (2024). Decoding Missense Variants by Incorporating Phase Separation via Machine Learning. Nature Communications. 15(1). 8279–8279. 5 indexed citations
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Xu, Honglin, et al.. (2024). Investigating TCR-pMHC interactions for TCRs without identified epitopes by constructing a computational pipeline. International Journal of Biological Macromolecules. 282(Pt 1). 136502–136502.
9.
Li, Keyi, et al.. (2023). 3D genome-selected microRNAs to improve Alzheimer's disease prediction. Frontiers in Neurology. 14. 1059492–1059492. 6 indexed citations
10.
Chen, Xia, Hao Yu, Ji Li, et al.. (2023). Structure and molecular basis of spermatid elongation in the Drosophila testis. Open Biology. 13(11). 230136–230136. 7 indexed citations
11.
Weng, Jialei, Shaoqing Liu, Qiang Zhou, et al.. (2023). Intratumoral PPT1-positive macrophages determine immunosuppressive contexture and immunotherapy response in hepatocellular carcinoma. Journal for ImmunoTherapy of Cancer. 11(6). e006655–e006655. 32 indexed citations
12.
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Su, Xianbin, Shihao Bai, Gangcai Xie, et al.. (2022). Accurate tumor clonal structures require single‐cell analysis. Annals of the New York Academy of Sciences. 1517(1). 213–224. 4 indexed citations
14.
Zhang, Xiao, Yunhua Xu, Lifang Ma, et al.. (2022). Essential roles of exosome and circRNA_101093 on ferroptosis desensitization in lung adenocarcinoma. Cancer Communications. 42(4). 287–313. 132 indexed citations breakdown →
15.
Cameron, Béatrice, et al.. (2022). An innovative strategy to identify new targets for delivering antibodies to the brain has led to the exploration of the integrin family. PLoS ONE. 17(9). e0274667–e0274667. 3 indexed citations
16.
Guo, Zhenming, Mengxia Chen, Liangjie Liu, et al.. (2021). RGCC balances self‐renewal and neuronal differentiation of neural stem cells in the developing mammalian neocortex. EMBO Reports. 22(9). e51781–e51781. 14 indexed citations
17.
Wu, Yanting, Ben W. Mol, Cheng Li, et al.. (2020). Early Prediction of Gestational Diabetes Mellitus in the Chinese Population via Advanced Machine Learning. The Journal of Clinical Endocrinology & Metabolism. 106(3). e1191–e1205. 115 indexed citations
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Zeitouni, Nathalie C., Ulaş Sunar, Daniel Rohrbach, et al.. (2014). A Prospective Study of Pain Control by a 2-Step Irradiance Schedule During Topical Photodynamic Therapy of Nonmelanoma Skin Cancer. Dermatologic Surgery. 40(12). 1390–1394. 18 indexed citations
20.
Li, Guangming, Yi Shi, Dingguo Li, et al.. (2004). [Effect of small interfering RNA targeting connective tissue growth factor on the synthesis and secretion of extracellular matrix in hepatic stellate cells].. PubMed. 12(9). 526–9. 3 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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