Pei-wu Yu

3.4k total citations · 1 hit paper
68 papers, 2.3k citations indexed

About

Pei-wu Yu is a scholar working on Oncology, Molecular Biology and Immunology. According to data from OpenAlex, Pei-wu Yu has authored 68 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Oncology, 20 papers in Molecular Biology and 20 papers in Immunology. Recurrent topics in Pei-wu Yu's work include Cancer Immunotherapy and Biomarkers (9 papers), Cytokine Signaling Pathways and Interactions (8 papers) and Cancer Cells and Metastasis (7 papers). Pei-wu Yu is often cited by papers focused on Cancer Immunotherapy and Biomarkers (9 papers), Cytokine Signaling Pathways and Interactions (8 papers) and Cancer Cells and Metastasis (7 papers). Pei-wu Yu collaborates with scholars based in China, Australia and United States. Pei-wu Yu's co-authors include Yongliang Zhao, Yuan Zhuang, Quanming Zou, Xiaolong Fu, Yong‐sheng Teng, Fangyuan Mao, Yan Shi, Liu‐sheng Peng, Feng Qian and Weisan Chen and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and Gut.

In The Last Decade

Pei-wu Yu

67 papers receiving 2.3k citations

Hit Papers

Tumour-activated neutrophils in gastric cancer foster imm... 2017 2026 2020 2023 2017 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pei-wu Yu China 25 823 785 769 530 447 68 2.3k
Kazuhiro Noma Japan 27 731 0.9× 420 0.5× 821 1.1× 331 0.6× 756 1.7× 126 2.3k
Tatsuo Shimura Japan 27 928 1.1× 845 1.1× 827 1.1× 292 0.6× 286 0.6× 144 2.5k
Yongliang Zhao China 31 693 0.8× 1.2k 1.5× 1.0k 1.3× 477 0.9× 1.1k 2.4× 88 3.1k
Baoqing Jia China 29 1.4k 1.7× 328 0.4× 632 0.8× 731 1.4× 292 0.7× 87 2.5k
Sophie S.W. Wang Taiwan 17 982 1.2× 309 0.4× 1.2k 1.6× 549 1.0× 397 0.9× 27 2.5k
Masahiko Nishizaki Japan 27 929 1.1× 160 0.2× 749 1.0× 272 0.5× 645 1.4× 79 2.2k
Masayasu Hara Japan 17 539 0.7× 271 0.3× 1.1k 1.4× 397 0.7× 279 0.6× 55 1.7k
Ho Sung Park South Korea 29 1.1k 1.4× 357 0.5× 1.1k 1.4× 430 0.8× 585 1.3× 123 2.9k
Hisashi Shinohara Japan 24 492 0.6× 301 0.4× 590 0.8× 161 0.3× 737 1.6× 85 1.9k

Countries citing papers authored by Pei-wu Yu

Since Specialization
Citations

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

Fields of papers citing papers by Pei-wu Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pei-wu Yu. 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 Pei-wu Yu. The network helps show where Pei-wu Yu may publish in the future.

Co-authorship network of co-authors of Pei-wu Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Pei-wu Yu. A scholar is included among the top collaborators of Pei-wu Yu 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 Pei-wu Yu. Pei-wu Yu 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.
Yu, Pei-wu, Yu Liu, Ming‐Yii Huang, et al.. (2025). Exon 13 skipping mediated by HNRNPL facilitates truncated SLK-induced metastasis in hepatocellular carcinoma. Biochemical Pharmacology. 242(Pt 4). 117390–117390.
2.
Chen, Feng, Pingang Li, Fan Zhang, Hua Chen, & Pei-wu Yu. (2020). A Meta-Analysis of the Association Between the VEGF +936C>T Gene Polymorphism and Digestive System Cancer Susceptibility. Genetic Testing and Molecular Biomarkers. 24(11). 732–744. 2 indexed citations
3.
Liu, Junyan, Lei Jiang, Jiajia Liu, et al.. (2018). AEBP1 promotes epithelial-mesenchymal transition of gastric cancer cells by activating the NF-κB pathway and predicts poor outcome of the patients. Scientific Reports. 8(1). 11955–11955. 41 indexed citations
4.
Wang, Tingting, Yongliang Zhao, Liu‐sheng Peng, et al.. (2017). Tumour-activated neutrophils in gastric cancer foster immune suppression and disease progression through GM-CSF-PD-L1 pathway. Gut. 66(11). 1900–1911. 384 indexed citations breakdown →
5.
Wang, Lin & Pei-wu Yu. (2016). miR-300 promotes proliferation and EMT-mediated colorectal cancer migration and invasion by targeting p53. Oncology Reports. 36(6). 3225–3232. 29 indexed citations
6.
Shi, Yajun, L. Wang, Baohui Han, et al.. (2016). First-line icotinib versus cisplatine/pemetrexed plus pemetrexed maintenance therapy in lung adenocarcinoma patients with EGFR mutation (CONVINCE). Annals of Oncology. 27. vi425–vi425. 2 indexed citations
7.
Shi, Yan, Pei-wu Yu, & Dong-zhu Zeng. (2014). Dose–response meta-analysis of poultry intake and colorectal cancer incidence and mortality. European Journal of Nutrition. 54(2). 243–250. 19 indexed citations
10.
Li, Fang, et al.. (2012). Association of hOGG1 Ser326Cys polymorphism with gastric cancer risk: a meta-analysis. Molecular Biology Reports. 39(6). 6563–6568. 3 indexed citations
11.
Wang, Pan, Chao Zhang, Pei-wu Yu, et al.. (2012). Regulation of colon cancer cell migration and invasion by CLIC1-mediated RVD. Molecular and Cellular Biochemistry. 365(1-2). 313–321. 49 indexed citations
12.
Peng, Liu‐sheng, Yuan Zhuang, Yun Shi, et al.. (2012). Increased tumor-infiltrating CD8+Foxp3+ T lymphocytes are associated with tumor progression in human gastric cancer. Cancer Immunology Immunotherapy. 61(11). 2183–2192. 49 indexed citations
13.
Luo, Hua-xing, Yingxue Hao, Bo Tang, et al.. (2012). Mouse forestomach carcinoma cells immunosuppress macrophages through transforming growth factor-β1. Molecular Medicine Reports. 5(4). 988–992. 13 indexed citations
14.
Liu, Tao, Liu‐sheng Peng, Pei-wu Yu, et al.. (2012). Increased Circulating Th22 and Th17 Cells are Associated with Tumor Progression and Patient Survival in Human Gastric Cancer. Journal of Clinical Immunology. 32(6). 1332–1339. 86 indexed citations
15.
Luo, Hua-xing, Pei-wu Yu, Hao Yue, et al.. (2011). Effects of CO<sub>2</sub> Pneumoperitoneum on Peritoneal Macrophage Function and Peritoneal Metastasis in Mice with Gastric Cancer. European Surgical Research. 48(1). 40–47. 2 indexed citations
16.
Hao, Yingxue, Pei-wu Yu, Chao Zhang, et al.. (2010). Effects of CO2 pneumoperitoneum pressures on growth and proliferation of gastric cancer cells in nude mice transplanted tumor. Zhonghua putong waike zazhi. 25(7). 572–574. 1 indexed citations
17.
Tang, Bo, Zhihong Peng, Pei-wu Yu, Ge Yu, & Feng Qian. (2010). Expression and significance of Cx43 and E-cadherin in gastric cancer and metastatic lymph nodes. Medical Oncology. 28(2). 502–508. 60 indexed citations
18.
Yu, Pei-wu. (2009). Antigen expression and cellular immunogenicity of NY-ESO-1 in gastric and esophageal cancer. Di-san junyi daxue xuebao. 1 indexed citations
19.
Hao, Yingxue, Hua Zhong, Pei-wu Yu, et al.. (2008). Effects of HIF-1α on human gastric cancer cell apoptosis at different CO2 pressures. Clinical and Experimental Medicine. 9(2). 139–147. 9 indexed citations
20.
Hao, Yingxue, et al.. (2008). Effects of simulated carbon dioxide and helium peumoperitoneum on proliferation and apoptosis of gastric cancer cells. World Journal of Gastroenterology. 14(14). 2241–2241. 8 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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