Wei‐Guo Tang

732 total citations
26 papers, 529 citations indexed

About

Wei‐Guo Tang is a scholar working on Molecular Biology, Cancer Research and Hepatology. According to data from OpenAlex, Wei‐Guo Tang has authored 26 papers receiving a total of 529 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 13 papers in Cancer Research and 5 papers in Hepatology. Recurrent topics in Wei‐Guo Tang's work include Cancer-related molecular mechanisms research (7 papers), Circular RNAs in diseases (5 papers) and Hepatocellular Carcinoma Treatment and Prognosis (4 papers). Wei‐Guo Tang is often cited by papers focused on Cancer-related molecular mechanisms research (7 papers), Circular RNAs in diseases (5 papers) and Hepatocellular Carcinoma Treatment and Prognosis (4 papers). Wei‐Guo Tang collaborates with scholars based in China, Ethiopia and India. Wei‐Guo Tang's co-authors include Bo Hu, Jia Fan, Qimeng Chang, Jin-Feng Feng, Ziping Zhang, Juxiang Zhang, Yang Xu, Jianfa Wang, Xubo Wu and Zhiqiu Hu and has published in prestigious journals such as Analytical Chemistry, Scientific Reports and Journal of Colloid and Interface Science.

In The Last Decade

Wei‐Guo Tang

24 papers receiving 526 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wei‐Guo Tang China 15 306 222 75 71 51 26 529
Xinjia He China 15 190 0.6× 75 0.3× 75 1.0× 56 0.8× 16 0.3× 32 518
Jinglin Li China 17 500 1.6× 484 2.2× 49 0.7× 44 0.6× 13 0.3× 28 787
Haiyan Yang China 14 381 1.2× 300 1.4× 63 0.8× 125 1.8× 31 0.6× 31 614
Lingqin Song China 16 358 1.2× 204 0.9× 106 1.4× 43 0.6× 8 0.2× 25 593
Yingyao Quan China 13 426 1.4× 320 1.4× 56 0.7× 62 0.9× 23 0.5× 17 615
Mingming Meng China 9 253 0.8× 150 0.7× 61 0.8× 42 0.6× 160 3.1× 22 695
Stavros P. Papadakos Greece 12 182 0.6× 61 0.3× 66 0.9× 46 0.6× 36 0.7× 43 417

Countries citing papers authored by Wei‐Guo Tang

Since Specialization
Citations

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

Fields of papers citing papers by Wei‐Guo Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wei‐Guo Tang. 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 Wei‐Guo Tang. The network helps show where Wei‐Guo Tang may publish in the future.

Co-authorship network of co-authors of Wei‐Guo Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Wei‐Guo Tang. A scholar is included among the top collaborators of Wei‐Guo Tang 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 Wei‐Guo Tang. Wei‐Guo Tang 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.
Tang, Wei‐Guo, Jin-Feng Feng, Xian Li, et al.. (2025). MCM3 promotes hepatocellular carcinoma progression via Epithelial-mesenchymal Transition through AKT/Twist signaling pathway. Annals of Hepatology. 30(1). 101785–101785.
2.
Zou, Mengyun, et al.. (2025). Immune-iron homeostasis deciphers resistance divergence to Riemerella anatipestifer in ducks. Frontiers in Microbiology. 16. 1627631–1627631.
3.
4.
Ma, Xiaolu, Suhong Xie, Hui Zheng, et al.. (2023). ASAP2 interrupts c-MET-CIN85 interaction to sustain HGF/c-MET-induced malignant potentials in hepatocellular carcinoma. Experimental Hematology and Oncology. 12(1). 38–38. 6 indexed citations
5.
Hu, Bo, Xiaolu Ma, Pei‐Yao Fu, et al.. (2021). The mRNA–miRNA–lncRNA Regulatory Network and Factors Associated with Prognosis Prediction of Hepatocellular Carcinoma. Genomics Proteomics & Bioinformatics. 19(6). 913–925. 20 indexed citations
6.
Hu, Jinwu, Guangyu Ding, Pei‐Yao Fu, et al.. (2020). Identification of FOS as a Candidate Risk Gene for Liver Cancer by Integrated Bioinformatic Analysis. BioMed Research International. 2020(1). 6784138–6784138. 15 indexed citations
7.
Tang, Wei‐Guo, et al.. (2020). Serum STIP1, a Novel Indicator for Microvascular Invasion, Predicts Outcomes and Treatment Response in Hepatocellular Carcinoma. Frontiers in Oncology. 10. 511–511. 15 indexed citations
8.
Zhang, Juxiang, Qimeng Chang, Xubo Wu, et al.. (2020). Correction to: LncRNA MYLK-AS1 facilitates tumor progression and angiogenesis by targeting miR-424-5p/E2F7 axis and activating VEGFR-2 signaling pathway in hepatocellular carcinoma. Journal of Experimental & Clinical Cancer Research. 39(1). 8 indexed citations
9.
Teng, Fei, Juxiang Zhang, Qimeng Chang, et al.. (2020). LncRNA MYLK-AS1 facilitates tumor progression and angiogenesis by targeting miR-424-5p/E2F7 axis and activating VEGFR-2 signaling pathway in hepatocellular carcinoma. Journal of Experimental & Clinical Cancer Research. 39(1). 235–235. 97 indexed citations
10.
Zhang, Yu, et al.. (2020). ABT-199 inhibits Hedgehog pathway by acting as a competitive inhibitor of oxysterol, rather as a BH3 mimetic. Acta Pharmacologica Sinica. 42(6). 1005–1013. 8 indexed citations
11.
Fu, Pei‐Yao, Bo Hu, Xiaolu Ma, et al.. (2019). Far upstream element-binding protein 1 facilitates hepatocellular carcinoma invasion and metastasis. Carcinogenesis. 41(7). 950–960. 13 indexed citations
12.
Zhou, Chenhao, Yue Zhao, Yirui Yin, et al.. (2019). A robust 6-mRNA signature for prognosis prediction of pancreatic ductal adenocarcinoma. International Journal of Biological Sciences. 15(11). 2282–2295. 15 indexed citations
13.
Hu, Bo, Hong Li, Wei Guo, et al.. (2019). Establishment of a hepatocellular carcinoma patient‐derived xenograft platform and its application in biomarker identification. International Journal of Cancer. 146(6). 1606–1617. 35 indexed citations
14.
Fu, Pei‐Yao, Bo Hu, Xiaolu Ma, et al.. (2018). New insight into BIRC3: A novel prognostic indicator and a potential therapeutic target for liver cancer. Journal of Cellular Biochemistry. 120(4). 6035–6045. 34 indexed citations
15.
He, Sheng, Bo Hu, Chao Li, et al.. (2018). PDXliver: a database of liver cancer patient derived xenograft mouse models. BMC Cancer. 18(1). 550–550. 24 indexed citations
16.
Chen, Wanyong, Chenhao Zhou, Wentao Zhang, et al.. (2018). Association of WWOX rs9926344 polymorphism with poor prognosis of hepatocellular carcinoma. Journal of Cancer. 9(7). 1239–1247. 10 indexed citations
17.
Sun, Qi‐Man, Bo Hu, Pei‐Yao Fu, et al.. (2018). Long non-coding RNA 00607 as a tumor suppressor by modulating NF-κB p65/p53 signaling axis in hepatocellular carcinoma. Carcinogenesis. 39(12). 1438–1446. 28 indexed citations
18.
Tang, Wei‐Guo, Bo Hu, Haixiang Sun, et al.. (2017). Long non-coding RNA00364 represses hepatocellular carcinoma cell proliferation via modulating p-STAT3-IFIT2 signaling axis. Oncotarget. 8(60). 102006–102019. 29 indexed citations
19.
Zhao, Longgang, Qingli Zhang, Jiali Zheng, et al.. (2016). Dietary, circulating beta-carotene and risk of all-cause mortality: a meta-analysis from prospective studies. Scientific Reports. 6(1). 26983–26983. 25 indexed citations
20.
Ma, Xiao, Wei‐Guo Tang, Yang Yang, et al.. (2016). Association between whole grain intake and all-cause mortality: a meta-analysis of cohort studies. Oncotarget. 7(38). 61996–62005. 18 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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