Run Shi

1.9k total citations
62 papers, 1.3k citations indexed

About

Run Shi is a scholar working on Molecular Biology, Immunology and Cancer Research. According to data from OpenAlex, Run Shi has authored 62 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 19 papers in Immunology and 19 papers in Cancer Research. Recurrent topics in Run Shi's work include Ferroptosis and cancer prognosis (13 papers), RNA modifications and cancer (8 papers) and Cancer-related molecular mechanisms research (7 papers). Run Shi is often cited by papers focused on Ferroptosis and cancer prognosis (13 papers), RNA modifications and cancer (8 papers) and Cancer-related molecular mechanisms research (7 papers). Run Shi collaborates with scholars based in China, Germany and United States. Run Shi's co-authors include Xuanwen Bao, Tianyu Zhao, Yanfang Wang, Kai Zhang, Claus Belka, Xin Shan, Minglun Li, Jing Sun, Chuan Su and Yanfang Wang and has published in prestigious journals such as Advanced Materials, SHILAP Revista de lepidopterología and Biomaterials.

In The Last Decade

Run Shi

56 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Run Shi China 23 685 423 365 321 233 62 1.3k
Heming Li China 19 506 0.7× 325 0.8× 192 0.5× 475 1.5× 150 0.6× 60 1.1k
Zhennan Yuan China 12 486 0.7× 324 0.8× 171 0.5× 278 0.9× 213 0.9× 30 1.1k
Dongjun Jeong South Korea 21 798 1.2× 294 0.7× 268 0.7× 528 1.6× 202 0.9× 55 1.6k
Kyoko Hida Japan 24 1.1k 1.6× 623 1.5× 193 0.5× 672 2.1× 298 1.3× 58 1.8k
Qijie Zhao China 17 593 0.9× 375 0.9× 157 0.4× 354 1.1× 290 1.2× 23 1.2k
Yao Yuan China 20 855 1.2× 376 0.9× 185 0.5× 500 1.6× 174 0.7× 72 1.6k
Joshua J. Souchek United States 16 462 0.7× 245 0.6× 201 0.6× 326 1.0× 99 0.4× 22 1.0k
V. М. Perelmuter Russia 20 511 0.7× 390 0.9× 192 0.5× 600 1.9× 160 0.7× 108 1.3k
Minyang Fu China 5 809 1.2× 224 0.5× 214 0.6× 510 1.6× 496 2.1× 7 1.6k
Ying Ma China 20 741 1.1× 310 0.7× 243 0.7× 620 1.9× 480 2.1× 81 1.7k

Countries citing papers authored by Run Shi

Since Specialization
Citations

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

Fields of papers citing papers by Run Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Run Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Run Shi. A scholar is included among the top collaborators of Run 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 Run Shi. Run 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.
2.
Huang, Dan, et al.. (2025). Regarding: ‘beyond inflammation: what drives the self-perpetuating cycle of fibrosis in IBD?’. Annals of Medicine. 57(1). 2597689–2597689.
3.
Shi, Run, et al.. (2025). Glucose Metabolism‐Targeted Poly(amino acid) Nanoformulation of Oxaliplatin(IV)‐Aspirin Prodrug for Enhanced Chemo‐Immunotherapy. Advanced Materials. 37(12). e2419033–e2419033. 12 indexed citations
4.
Shi, Run, Ya Xu, Tingting Xu, et al.. (2025). Multi-omics and single-cell analysis reveals machine learning-based pyrimidine metabolism-related signature in the prognosis of patients with lung adenocarcinoma. International Journal of Medical Sciences. 22(6). 1375–1392. 1 indexed citations
5.
Shi, Run, William C. Cho, You Yeon Choi, et al.. (2024). Bioinformatics-based analysis of fatty acid metabolic reprogramming in hepatocellular carcinoma: cellular heterogeneity, therapeutic targets, and drug discovery. SHILAP Revista de lepidopterología. 3(4). 1 indexed citations
6.
Wei, Hongyan, Ke Yi, Di Li, et al.. (2023). Multimodal Tetrahedral DNA Nanoplatform for Surprisingly Rapid and Significant Treatment of Acute Liver Failure. Advanced Materials. 36(30). e2305826–e2305826. 31 indexed citations
7.
Kong, Huimin, Fangfang Cao, Chenya Zhuo, et al.. (2023). Anti–phagocytosis-blocking repolarization-resistant membrane-fusogenic liposome (ARMFUL) for adoptive cell immunotherapy. Science Advances. 9(32). eadh2413–eadh2413. 43 indexed citations
8.
9.
Lü, Wei, Sanyuan Ma, Le Sun, et al.. (2023). Combined CRISPR toolkits reveal the domestication landscape and function of the ultra-long and highly repetitive silk genes. Acta Biomaterialia. 158. 190–202. 11 indexed citations
10.
Gao, Shanshan, Run Shi, Jing Sun, et al.. (2022). GPI-anchored ligand-BioID2-tagging system identifies Galectin-1 mediating Zika virus entry. iScience. 25(12). 105481–105481. 4 indexed citations
11.
Jia, Jia, Hongliang Li, Run Shi, et al.. (2022). Adjuvant effects of Chinese medicinal tonics on gastric, liver, and colorectal cancers—OMICs-based contributions to understanding their mechanism of action. Frontiers in Pharmacology. 13. 986765–986765. 2 indexed citations
12.
Zhang, Quanli, Run Shi, Yongkang Bai, et al.. (2021). Meiotic nuclear divisions 1 (MND1) fuels cell cycle progression by activating a KLF6/E2F1 positive feedback loop in lung adenocarcinoma. Cancer Communications. 41(6). 492–510. 26 indexed citations
13.
Wang, Xin, Uris Ros, Julia Slotta‐Huspenina, et al.. (2021). MLKL promotes cellular differentiation in myeloid leukemia by facilitating the release of G-CSF. Cell Death and Differentiation. 28(12). 3235–3250. 12 indexed citations
14.
Bao, Xuanwen, Run Shi, Tianyu Zhao, & Yanfang Wang. (2020). Immune landscape and a novel immunotherapy-related gene signature associated with clinical outcome in early-stage lung adenocarcinoma. Journal of Molecular Medicine. 98(6). 805–818. 16 indexed citations
15.
Bao, Xuanwen, Run Shi, Tianyu Zhao, & Yanfang Wang. (2020). Mast cell‐based molecular subtypes and signature associated with clinical outcome in early‐stage lung adenocarcinoma. Molecular Oncology. 14(5). 917–932. 44 indexed citations
16.
Bao, Xuanwen, Run Shi, Tianyu Zhao, et al.. (2020). Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels tumour heterogeneity plus M2-like tumour-associated macrophage infiltration and aggressiveness in TNBC. Cancer Immunology Immunotherapy. 70(1). 189–202. 99 indexed citations
17.
Sun, Jing, Tianyu Zhao, Di Zhao, et al.. (2020). Development and validation of a hypoxia-related gene signature to predict overall survival in early-stage lung adenocarcinoma patients. Therapeutic Advances in Medical Oncology. 12. 3863552944–3863552944. 43 indexed citations
18.
Shi, Run, Shanshan Gao, Huan Li, et al.. (2020). Superoxide-induced Type I collagen secretion depends on prolyl 4-hydroxylases. Biochemical and Biophysical Research Communications. 529(4). 1011–1017. 15 indexed citations
19.
20.
Liu, Li, et al.. (2008). Protective Effect of Saponins from Panax notoginseng against Doxorubicin-Induced Cardiotoxicity in Mice. Planta Medica. 74(3). 203–209. 28 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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