Sheng Tai

5.0k total citations · 1 hit paper
110 papers, 3.6k citations indexed

About

Sheng Tai is a scholar working on Molecular Biology, Surgery and Cancer Research. According to data from OpenAlex, Sheng Tai has authored 110 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Molecular Biology, 32 papers in Surgery and 32 papers in Cancer Research. Recurrent topics in Sheng Tai's work include MicroRNA in disease regulation (16 papers), Cancer-related molecular mechanisms research (16 papers) and Cholangiocarcinoma and Gallbladder Cancer Studies (12 papers). Sheng Tai is often cited by papers focused on MicroRNA in disease regulation (16 papers), Cancer-related molecular mechanisms research (16 papers) and Cholangiocarcinoma and Gallbladder Cancer Studies (12 papers). Sheng Tai collaborates with scholars based in China, United States and United Kingdom. Sheng Tai's co-authors include Chang Yin Liang, Allan Tsung, Hai Huang, Patricia Loughran, Samer Tohme, Jiaoti Huang, William Oh, Hong Zhang, Yin Sun and Jill Squires and has published in prestigious journals such as PLoS ONE, Biomaterials and Hepatology.

In The Last Decade

Sheng Tai

105 papers receiving 3.6k citations

Hit Papers

Damage‐associated molecular pattern–activated neutrophil ... 2015 2026 2018 2022 2015 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sheng Tai China 29 1.7k 1.0k 786 528 478 110 3.6k
Zakaria Y. Abd Elmageed United States 31 1.6k 1.0× 824 0.8× 324 0.4× 335 0.6× 583 1.2× 94 2.9k
Karin Müller‐Decker Germany 38 2.0k 1.2× 831 0.8× 537 0.7× 259 0.5× 654 1.4× 87 4.6k
Nianzeng Xing China 27 1.1k 0.7× 518 0.5× 445 0.6× 631 1.2× 489 1.0× 164 3.1k
Yu‐Jia Chang Taiwan 35 2.2k 1.3× 590 0.6× 359 0.5× 494 0.9× 764 1.6× 153 4.0k
Yasuyoshi Miyata Japan 33 1.5k 0.9× 608 0.6× 256 0.3× 570 1.1× 641 1.3× 174 3.3k
Jiawei Chen China 32 1.3k 0.8× 727 0.7× 1.0k 1.3× 204 0.4× 365 0.8× 131 3.2k
Bicheng Chen China 31 1.6k 1.0× 792 0.8× 246 0.3× 276 0.5× 567 1.2× 129 3.3k
Yen‐Chuan Ou Taiwan 34 1.1k 0.7× 306 0.3× 307 0.4× 827 1.6× 351 0.7× 223 3.9k
Quan Hong China 38 1.9k 1.2× 577 0.6× 479 0.6× 314 0.6× 270 0.6× 194 4.2k
Xiangyi Zheng China 39 2.4k 1.4× 1.7k 1.6× 151 0.2× 691 1.3× 470 1.0× 138 4.1k

Countries citing papers authored by Sheng Tai

Since Specialization
Citations

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

Fields of papers citing papers by Sheng Tai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sheng Tai

This figure shows the co-authorship network connecting the top 25 collaborators of Sheng Tai. A scholar is included among the top collaborators of Sheng Tai 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 Sheng Tai. Sheng Tai 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.
Tai, Sheng, Ye Wang, Sunyi Ye, et al.. (2025). Safety and reliability of telesurgery in China: a multicenter, single-arm, phase I clinical trial. International Journal of Surgery. 111(10). 6678–6687. 1 indexed citations
3.
Xu, Wenlong, Junyang Yue, Yi Zhang, et al.. (2025). Juglone alleviates pelvic pain and prostatic inflammation via inhibiting the activation of NLRP3 inflammasome and alleviating oxidative stress in EAP mice. Phytomedicine. 142. 156732–156732. 2 indexed citations
5.
Wu, Dehai, Guanqun Liao, Liang Ming, et al.. (2024). Identified a novel prognostic model of HCC basing on virus signature for guiding immunotherapy. Discover Oncology. 15(1). 551–551. 1 indexed citations
7.
Wang, Haoran, et al.. (2024). Construction of m7G RNA modification-related prognostic model and prediction of immune therapy response in hepatocellular carcinoma. Translational Cancer Research. 13(6). 2799–2811. 2 indexed citations
8.
Tai, Sheng, Dandan Xu, Zhixian Yu, et al.. (2023). Genomic profiles of renal cell carcinoma in a small Chinese cohort. Frontiers in Oncology. 13. 1095775–1095775. 5 indexed citations
9.
Hua, Xiaoliang, Jiong Zhang, Haibing Xiao, et al.. (2021). A costimulatory molecule-related signature in regard to evaluation of prognosis and immune features for clear cell renal cell carcinoma. Cell Death Discovery. 7(1). 252–252. 14 indexed citations
10.
Hua, Xiaoliang, Meng Zhang, Fan Mo, et al.. (2021). Pathogenic Roles of CXCL10 in Experimental Autoimmune Prostatitis by Modulating Macrophage Chemotaxis and Cytokine Secretion. Frontiers in Immunology. 12. 706027–706027. 39 indexed citations
11.
Liu, Gang, Chang Yin Liang, Zongyao Hao, et al.. (2021). Outcomes of Robot-Assisted Laparoscopic Isthmus Division Using Endoscopic Transection Equipment in the Treatment of Symptomatic Horseshoe Kidney. Journal of Laparoendoscopic & Advanced Surgical Techniques. 32(6). 646–652. 1 indexed citations
12.
Hua, Xiaoliang, Juan Chen, Haibing Xiao, et al.. (2021). Identification of a Costimulatory Molecule-Related Signature for Predicting Prognostic Risk in Prostate Cancer. Frontiers in Genetics. 12. 666300–666300. 13 indexed citations
13.
Yang, Lin, Delin Kong, Mei He, et al.. (2020). MiR-7 mediates mitochondrial impairment to trigger apoptosis and necroptosis in Rhabdomyosarcoma. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research. 1867(12). 118826–118826. 28 indexed citations
14.
Yazdani, Hamza O., Dirk J. van der Windt, Hongji Zhang, et al.. (2019). Neutrophil Extracellular Traps Drive Mitochondrial Homeostasis in Tumors to Augment Growth. Cancer Research. 79(21). 5626–5639. 213 indexed citations
15.
Tai, Sheng, et al.. (2019). Oncogenicity of lncRNA FOXD2-AS1 and its molecular mechanisms in human cancers. Pathology - Research and Practice. 215(5). 843–848. 27 indexed citations
16.
Zhou, Jun, et al.. (2019). Endoscopic robot‐assisted simple enucleation of renal tumours: Impact of learning curve and tumour complexity on trifecta outcomes. International Journal of Medical Robotics and Computer Assisted Surgery. 15(4). e2000–e2000. 1 indexed citations
17.
Kang, Pengcheng, Ming Wan, Peng Huang, et al.. (2014). The Wnt Antagonist sFRP1 as a Favorable Prognosticator in Human Biliary Tract Carcinoma. PLoS ONE. 9(3). e90308–e90308. 24 indexed citations
18.
Tai, Sheng, Yin Sun, Nan Liu, et al.. (2012). Combination of Rad001 (Everolimus) and Propachlor Synergistically Induces Apoptosis through Enhanced Autophagy in Prostate Cancer Cells. Molecular Cancer Therapeutics. 11(6). 1320–1331. 24 indexed citations
19.
Liu, Nan, Sheng Tai, Boxiao Ding, et al.. (2012). Arsenic trioxide synergizes with everolimus (Rad001) to induce cytotoxicity of ovarian cancer cells through increased autophagy and apoptosis. Endocrine Related Cancer. 19(5). 711–723. 23 indexed citations
20.
Zhang, Yong, Jianwei Ye, Dazhi Chen, et al.. (2006). Differential expression profiling between the relative normal and dystrophic muscle tissues from the same LGMD patient. Journal of Translational Medicine. 4(1). 53–53. 23 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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