Bangbao Tao

2.0k total citations
40 papers, 1.5k citations indexed

About

Bangbao Tao is a scholar working on Molecular Biology, Cancer Research and Pathology and Forensic Medicine. According to data from OpenAlex, Bangbao Tao has authored 40 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 15 papers in Cancer Research and 10 papers in Pathology and Forensic Medicine. Recurrent topics in Bangbao Tao's work include MicroRNA in disease regulation (7 papers), Trigeminal Neuralgia and Treatments (7 papers) and Cancer-related molecular mechanisms research (6 papers). Bangbao Tao is often cited by papers focused on MicroRNA in disease regulation (7 papers), Trigeminal Neuralgia and Treatments (7 papers) and Cancer-related molecular mechanisms research (6 papers). Bangbao Tao collaborates with scholars based in China, United States and Bulgaria. Bangbao Tao's co-authors include Shiting Li, Ji Liang, Weiwei Yang, Yajuan Zhang, Wenfeng Li, Xiongjun Wang, Ruilong Liu, Xiaoqiang Wang, Huiying Chu and Jun Zhong and has published in prestigious journals such as Nature Communications, ACS Nano and Molecular Cell.

In The Last Decade

Bangbao Tao

39 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bangbao Tao China 21 786 506 241 181 171 40 1.5k
Lixuan Yang China 18 956 1.2× 549 1.1× 118 0.5× 104 0.6× 84 0.5× 42 1.4k
Yong Yan China 26 821 1.0× 391 0.8× 109 0.5× 147 0.8× 82 0.5× 89 1.7k
Zhiyuan Zhu China 19 554 0.7× 340 0.7× 196 0.8× 125 0.7× 39 0.2× 46 1.2k
Ping He United States 24 1.0k 1.3× 288 0.6× 125 0.5× 258 1.4× 66 0.4× 51 1.8k
Arantxa Ortega‐Aznar Spain 19 676 0.9× 304 0.6× 179 0.7× 114 0.6× 55 0.3× 27 1.7k
Xiuping Zhou China 24 976 1.2× 299 0.6× 115 0.5× 253 1.4× 109 0.6× 74 1.6k
Gail Walkinshaw United States 19 566 0.7× 428 0.8× 96 0.4× 67 0.4× 181 1.1× 30 1.5k
Wanli Dong China 16 349 0.4× 196 0.4× 101 0.4× 134 0.7× 44 0.3× 53 971
Elena Rapizzi Italy 25 1.4k 1.8× 606 1.2× 117 0.5× 388 2.1× 52 0.3× 61 2.5k
Xiaoyan Zhu China 17 521 0.7× 187 0.4× 119 0.5× 204 1.1× 74 0.4× 50 1.1k

Countries citing papers authored by Bangbao Tao

Since Specialization
Citations

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

Fields of papers citing papers by Bangbao Tao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bangbao Tao

This figure shows the co-authorship network connecting the top 25 collaborators of Bangbao Tao. A scholar is included among the top collaborators of Bangbao Tao 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 Bangbao Tao. Bangbao Tao 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.
Xu, Wei, Zhipeng Guo, Xue Gao, et al.. (2025). Machine learning-based proteomics profiling of ALS identifies downregulation of RPS29 that maintains protein homeostasis and STMN2 level. Communications Biology. 8(1). 1177–1177.
2.
Zhang, Jian, Jiping Liu, Chen Wang, et al.. (2024). Generation of patient-derived glioblastoma organoids: a comparative study of enzymatic digestion and mechanical fragmentation methods. 1(2). 9410004–9410004. 3 indexed citations
3.
Fang, Xin, Leilei Guo, Zikang Xing, et al.. (2022). IDO1 can impair NK cells function against non-small cell lung cancer by downregulation of NKG2D Ligand via ADAM10. Pharmacological Research. 177. 106132–106132. 34 indexed citations
4.
Wu, Siyang, Bangbao Tao, Ping Wu, et al.. (2022). Pyruvate Facilitates FACT‐Mediated γH2AX Loading to Chromatin and Promotes the Radiation Resistance of Glioblastoma. Advanced Science. 9(8). e2104055–e2104055. 27 indexed citations
5.
Xing, Zikang, Bangbao Tao, Tianqi Li, et al.. (2020). Both IDO1 and TDO contribute to the malignancy of gliomas via the Kyn–AhR–AQP4 signaling pathway. Signal Transduction and Targeted Therapy. 5(1). 10–10. 108 indexed citations
6.
Tao, Bangbao, Yiqun Ling, Youyou Zhang, et al.. (2019). CA10 and CA11 negatively regulate neuronal activity‐dependent growth of gliomas. Molecular Oncology. 13(5). 1018–1032. 13 indexed citations
7.
Zeng, Xianwei, Bin Li, Bangbao Tao, et al.. (2019). Overexpression of immunoproteasome low-molecular-mass polypeptide 7 and inhibiting role of next-generation proteasome inhibitor ONX 0912 on cell growth in glioma. Neuroreport. 30(15). 1031–1038. 3 indexed citations
8.
Zhang, Wenbo, et al.. (2019). Hypertension and Diabetes Are Associated With Clinical Characteristics in Patients Undergoing Microvascular Decompression for Hemifacial Spasm. Journal of Craniofacial Surgery. 31(2). 468–471. 4 indexed citations
9.
Wang, Xiongjun, Ruilong Liu, Xiujuan Qu, et al.. (2019). α-Ketoglutarate-Activated NF-κB Signaling Promotes Compensatory Glucose Uptake and Brain Tumor Development. Molecular Cell. 76(1). 148–162.e7. 112 indexed citations
10.
Li, Shu, Shu Li, Wenhao Zhang, et al.. (2018). HOXC10 promotes proliferation and invasion and induces immunosuppressive gene expression in glioma. FEBS Journal. 285(12). 2278–2291. 38 indexed citations
11.
Gao, Hongliang, Yan Yuan, Qi Chen, et al.. (2017). Identification of a gene signature associated with radiotherapy and prognosis in gliomas. Oncotarget. 8(51). 88974–88987. 13 indexed citations
12.
Wang, Xiaoqiang, Hongmin Bai, Shiting Li, et al.. (2017). Knockdown of HDAC1 expression suppresses invasion and induces apoptosis in glioma cells. Oncotarget. 8(29). 48027–48040. 38 indexed citations
13.
Tao, Bangbao, Xiqiang Liu, Wenhao Zhang, et al.. (2017). Evidence for the association of chromatin and microRNA regulation in the human genome. Oncotarget. 8(41). 70958–70966. 16 indexed citations
14.
Zhao, Zhenyu, Hua He, Chunlin Wang, et al.. (2015). Downregulation of Id2 increases chemosensitivity of glioma. Tumor Biology. 36(6). 4189–4196. 16 indexed citations
15.
Li, Bin, Mingzhu Huang, Xiaoqiang Wang, et al.. (2015). TMEM140 is associated with the prognosis of glioma by promoting cell viability and invasion. Journal of Hematology & Oncology. 8(1). 101–101. 34 indexed citations
16.
He, Hua, Maojin Yao, Wenhao Zhang, et al.. (2015). MEK2 is a prognostic marker and potential chemo-sensitizing target for glioma patients undergoing temozolomide treatment. Cellular and Molecular Immunology. 13(5). 658–668. 9 indexed citations
17.
Zhong, Jun, Jin Zhu, Hui Sun, et al.. (2014). Microvascular decompression surgery: surgical principles and technical nuances based on 4000 cases. Neurological Research. 36(10). 882–893. 86 indexed citations
18.
Tao, Bangbao, Hua He, Qingfang Sun, et al.. (2012). MicroRNAs-based network: A novel therapeutic agent in pituitary adenoma. Medical Hypotheses. 78(3). 380–384. 21 indexed citations
19.
Li, Weiqing, Yiming Li, Bangbao Tao, et al.. (2010). MicroRNA-328 may contribute to chemoresistance in glioblastoma cancer stem cells by targeting ABCG2. Medical Science Monitor. 16(10). 3 indexed citations
20.
Ma, Dexuan, Bangbao Tao, Susumu Kotani, et al.. (2007). Expression of free fatty acid receptor GPR40 in the central nervous system of adult monkeys. Neuroscience Research. 58(4). 394–401. 92 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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