Yeming Wu

1.4k total citations · 1 hit paper
31 papers, 1.0k citations indexed

About

Yeming Wu is a scholar working on Neurology, Molecular Biology and Cancer Research. According to data from OpenAlex, Yeming Wu has authored 31 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Neurology, 16 papers in Molecular Biology and 10 papers in Cancer Research. Recurrent topics in Yeming Wu's work include Neuroblastoma Research and Treatments (16 papers), Cancer, Hypoxia, and Metabolism (8 papers) and Ubiquitin and proteasome pathways (5 papers). Yeming Wu is often cited by papers focused on Neuroblastoma Research and Treatments (16 papers), Cancer, Hypoxia, and Metabolism (8 papers) and Ubiquitin and proteasome pathways (5 papers). Yeming Wu collaborates with scholars based in China, United States and United Kingdom. Yeming Wu's co-authors include Lunzhi Dai, Yingming Zhao, Minjia Tan, Jef D. Boeke, Junbiao Dai, Zhongyi Cheng, Zhongyu Xie, Zhixiang Wu, Qiu-Dong Jiang and Jin‐Ao Duan and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and Cancer Research.

In The Last Decade

Yeming Wu

30 papers receiving 1.0k citations

Hit Papers

Lysine Succinylation and Lysine Malonylation in Histones 2012 2026 2016 2021 2012 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
Yeming Wu China 14 675 159 117 104 89 31 1.0k
Parul Gupta India 13 563 0.8× 115 0.7× 106 0.9× 42 0.4× 85 1.0× 26 846
Chandra Sekhar Bhol India 19 800 1.2× 221 1.4× 111 0.9× 61 0.6× 56 0.6× 33 1.2k
Rosalba Minelli Italy 19 478 0.7× 118 0.7× 178 1.5× 12 0.1× 32 0.4× 33 1.0k
Kewal Kumar Mahapatra India 17 781 1.2× 237 1.5× 111 0.9× 64 0.6× 51 0.6× 30 1.2k
Linlin Chang China 17 606 0.9× 143 0.9× 134 1.1× 26 0.3× 60 0.7× 48 1.0k
Appu Rathinavelu United States 18 599 0.9× 203 1.3× 241 2.1× 14 0.1× 60 0.7× 71 1.1k
Neelu Yadav United States 23 1.7k 2.4× 209 1.3× 137 1.2× 32 0.3× 74 0.8× 36 2.0k
Ramachandran Rashmi United States 15 717 1.1× 169 1.1× 136 1.2× 33 0.3× 42 0.5× 18 1.0k
Edwina N. Scott United Kingdom 10 430 0.6× 66 0.4× 281 2.4× 270 2.6× 39 0.4× 12 956

Countries citing papers authored by Yeming Wu

Since Specialization
Citations

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

Fields of papers citing papers by Yeming Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yeming Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Yeming Wu. A scholar is included among the top collaborators of Yeming Wu 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 Yeming Wu. Yeming Wu 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.
Desai, Ami V., Amy E. Armstrong, Cornelis M. van Tilburg, et al.. (2025). Efficacy and safety of entrectinib in children with extracranial solid or central nervous system (CNS) tumours harbouring NTRK or ROS1 fusions. European Journal of Cancer. 220. 115308–115308. 1 indexed citations
2.
Hu, Xiaoxiao, Yilu Zhou, Charlotte Hill, et al.. (2024). Identification of MYCN non-amplified neuroblastoma subgroups points towards molecular signatures for precision prognosis and therapy stratification. British Journal of Cancer. 130(11). 1841–1854. 3 indexed citations
3.
Liu, Xiaowei, Cheng Cheng, Xiaoxiao Hu, et al.. (2022). PCLAF promotes neuroblastoma G1/S cell cycle progression via the E2F1/PTTG1 axis. Cell Death and Disease. 13(2). 178–178. 31 indexed citations
4.
Cheng, Cheng, et al.. (2022). KHSRP modulated cell proliferation and cell cycle via regulating PPP2CA and p27 expression in Wilms tumor. Cellular Signalling. 100. 110447–110447. 6 indexed citations
5.
Cheng, Cheng, et al.. (2021). 15,16-dihydrotanshinone I inhibits EOMA cells proliferation by interfering in posttranscriptional processing of hypoxia-inducible factor 1. International Journal of Medical Sciences. 18(14). 3214–3223. 5 indexed citations
6.
Cheng, Cheng, et al.. (2021). XPO1/CRM1 is a promising prognostic indicator for neuroblastoma and represented a therapeutic target by selective inhibitor verdinexor. Journal of Experimental & Clinical Cancer Research. 40(1). 255–255. 19 indexed citations
7.
Chen, Kai, Cheng Cheng, Junqi Zhang, et al.. (2020). MYT1 attenuates neuroblastoma cell differentiation by interacting with the LSD1/CoREST complex. Oncogene. 39(21). 4212–4226. 13 indexed citations
8.
Chen, Kai, et al.. (2020). Prp19 Is an Independent Prognostic Marker and Promotes Neuroblastoma Metastasis by Regulating the Hippo-YAP Signaling Pathway. Frontiers in Oncology. 10. 575366–575366. 13 indexed citations
9.
Gu, Yuting, Mingxing Xue, Kai Chen, et al.. (2018). The deubiquitinating enzyme UCHL1 is a favorable prognostic marker in neuroblastoma as it promotes neuronal differentiation. Journal of Experimental & Clinical Cancer Research. 37(1). 258–258. 34 indexed citations
10.
Gu, Yuting, Xinyuan Ding, Jiefang Huang, et al.. (2018). The deubiquitinating enzyme UCHL1 negatively regulates the immunosuppressive capacity and survival of multipotent mesenchymal stromal cells. Cell Death and Disease. 9(5). 459–459. 38 indexed citations
12.
Zhang, Min, et al.. (2017). Legumain correlates with neuroblastoma differentiation and can be used in prodrug design. Chemical Biology & Drug Design. 91(2). 534–544. 6 indexed citations
13.
Wang, Yue, Yongtao Xiao, Kai Chen, et al.. (2016). Enhancer of zeste homolog 2 depletion arrests the proliferation of hepatoblastoma cells. Molecular Medicine Reports. 13(3). 2724–2728. 3 indexed citations
14.
Chen, Sheng, et al.. (2016). Exposure to pyrethroid pesticides and the risk of childhood brain tumors in East China. Environmental Pollution. 218. 1128–1134. 70 indexed citations
15.
Chen, Sheng, et al.. (2015). HIF-1α Contributes to Proliferation and Invasiveness of Neuroblastoma Cells via SHH Signaling. PLoS ONE. 10(3). e0121115–e0121115. 47 indexed citations
16.
Wu, Yeming, et al.. (2014). Preliminary analysis of stem cell-like cells in human neuroblastoma. World Journal of Pediatrics. 11(1). 54–60. 9 indexed citations
17.
Xu, Guofeng, et al.. (2013). Botryoid Wilms’ tumor: a case report and review of the literature. World Journal of Surgical Oncology. 11(1). 102–102. 7 indexed citations
18.
Xu, Guofeng, et al.. (2013). The Combined Effect of Retinoic Acid and LSD1 siRNA Inhibition on Cell Death in the Human Neuroblastoma Cell Line SH-SY5Y. Cellular Physiology and Biochemistry. 31(6). 854–862. 5 indexed citations
19.
Du, Lei, et al.. (2013). Role of surgery in the treatment of patients with high-risk neuroblastoma who have a poor response to induction chemotherapy. Journal of Pediatric Surgery. 49(4). 528–533. 16 indexed citations
20.
Xie, Zhongyu, Junbiao Dai, Lunzhi Dai, et al.. (2012). Lysine Succinylation and Lysine Malonylation in Histones. Molecular & Cellular Proteomics. 11(5). 100–107. 484 indexed citations breakdown →

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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