Shaofang Wu

779 total citations
21 papers, 459 citations indexed

About

Shaofang Wu is a scholar working on Molecular Biology, Oncology and Genetics. According to data from OpenAlex, Shaofang Wu has authored 21 papers receiving a total of 459 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 10 papers in Oncology and 9 papers in Genetics. Recurrent topics in Shaofang Wu's work include Glioma Diagnosis and Treatment (9 papers), DNA Repair Mechanisms (7 papers) and Cancer-related Molecular Pathways (5 papers). Shaofang Wu is often cited by papers focused on Glioma Diagnosis and Treatment (9 papers), DNA Repair Mechanisms (7 papers) and Cancer-related Molecular Pathways (5 papers). Shaofang Wu collaborates with scholars based in United States, China and Mexico. Shaofang Wu's co-authors include Dimpy Koul, W.K. Alfred Yung, Siyuan Zheng, Feng Gao, Lihong Chen, Jiandong Chen, John de Groot, Xiaolong Li, E. Schönbrunn and Andreas Becker and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Shaofang Wu

21 papers receiving 456 citations

Peers

Shaofang Wu

ONCOL

GENET

Christoph Heyder Germany

Serguei R. Romanov United States

Deepti B. Ramnarain United States

Maurice Reimann Germany

Kiyoung Eun South Korea

Han-Sui Hsu Taiwan

Sheila Figel United States

Ivana Samaržija Croatia

Amanda R. Wasylishen United States

Susanna Tronnersjö Sweden

Christoph Heyder Germany

Shaofang Wu

217 ×0.6

174 ×1.0

ONCOL

138 ×1.2

GENET

52 ×0.5

42 ×1.0

Citations per year, relative to Shaofang Wu Shaofang Wu (= 1×) peers Christoph Heyder

Countries citing papers authored by Shaofang Wu

Since Specialization

Citations

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

Fields of papers citing papers by Shaofang Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shaofang Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Shaofang Wu. A scholar is included among the top collaborators of Shaofang 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 Shaofang Wu. Shaofang Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Khan, Sabbir, Pratibha Sharma, Shaofang Wu, et al.. (2023). MGMT function determines the differential response of ATR inhibitors with DNA-damaging agents in glioma stem cells for GBM therapy. Neuro-Oncology Advances. 6(1). vdad165–vdad165. 5 indexed citations

Wu, Shaofang, Xiaolong Li, Feng Gao, et al.. (2021). PARP-mediated PARylation of MGMT is critical to promote repair of temozolomide-induced O6-methylguanine DNA damage in glioblastoma. Neuro-Oncology. 23(6). 920–931. 93 indexed citations

Noureen, Nighat, Shaofang Wu, Yingli Lv, et al.. (2021). Integrated analysis of telomerase enzymatic activity unravels an association with cancer stemness and proliferation. Nature Communications. 12(1). 139–139. 41 indexed citations

Koul, Dimpy, Xiao‐Long Li, Shaofang Wu, et al.. (2021). EXTH-06. ATR INHIBITORS AS MONOTHERAPY AND COMBINATORIAL THERAPY WITH TEMOZOLOMIDE IN PRECLINICAL GLIOBLASTOMA MODELS. Neuro-Oncology. 23(Supplement_6). vi164–vi164. 1 indexed citations

Wu, Shaofang, Feng Gao, Siyuan Zheng, et al.. (2019). EGFR Amplification Induces Increased DNA Damage Response and Renders Selective Sensitivity to Talazoparib (PARP Inhibitor) in Glioblastoma. Clinical Cancer Research. 26(6). 1395–1407. 34 indexed citations

Li, Xiaolong, Emmanuel Martínez-Ledesma, Chen Zhang, et al.. (2019). Tie2–FGFR1 Interaction Induces Adaptive PI3K Inhibitor Resistance by Upregulating Aurora A/PLK1/CDK1 Signaling in Glioblastoma. Cancer Research. 79(19). 5088–5101. 20 indexed citations

Wu, Shaofang, Feng Gao, Dimpy Koul, & Alfred Yung. (2019). DRES-02. PARYLATION OF MGMT BY PARP IS REQUIRED FOR MGMT MEDIATED TEMOZOLOMIDE-INDUCED O6-METHYLGUANINE REPAIR: A NOVEL MECHANISM OF MGMT ACTION. Neuro-Oncology. 21(Supplement_6). vi71–vi72. 2 indexed citations

Ding, Jie, Shaofang Wu, Chen Zhang, et al.. (2019). BRCA1 identified as a modulator of temozolomide resistance in P53 wild-type GBM using a high-throughput shRNA-based synthetic lethality screening.. PubMed. 9(11). 2428–2441. 8 indexed citations

Yung, W. K. Alfred, Shaofang Wu, Feng Gao, et al.. (2019). EGFR amplification predicted selective sensitivity to PARP inhibitors with high PARP-DNA trapping potential in human GBM.. Journal of Clinical Oncology. 37(15_suppl). 2047–2047. 1 indexed citations

10.

Zhang, Chen, Emmanuel Martínez-Ledesma, Feng Gao, et al.. (2019). Wild-type TP53 defined gamma-secretase inhibitor sensitivity and synergistic activity with doxorubicin in GSCs.. PubMed. 9(8). 1734–1745. 6 indexed citations

11.

Cai, Yi, Shaofang Wu, Su Q, et al.. (2018). Associations of TF Gene Polymorphisms with the Risk of Ischemic Stroke. Journal of Molecular Neuroscience. 65(3). 359–366. 1 indexed citations

12.

Dong, Jian‐Wen, Soon Young Park, Nghi Nguyen, et al.. (2018). The polo-like kinase 1 inhibitor volasertib synergistically increases radiation efficacy in glioma stem cells. Oncotarget. 9(12). 10497–10509. 15 indexed citations

13.

Su, Jiangshuo, Fei Zhang, Shaofang Wu, et al.. (2017). Dynamic and epistatic QTL mapping reveals the complex genetic architecture of waterlogging tolerance in chrysanthemum. Planta. 247(4). 899–924. 21 indexed citations

14.

Koul, Dimpy, Shuzhen Wang, Shaofang Wu, et al.. (2017). Preclinical therapeutic efficacy of a novel blood-brain barrier-penetrant dual PI3K/mTOR inhibitor with preferential response in PI3K/PTEN mutant glioma. Oncotarget. 8(13). 21741–21753. 16 indexed citations

15.

Wu, Shaofang, Shuzhen Wang, Feng Gao, et al.. (2017). Activation of WEE1 confers resistance to PI3K inhibition in glioblastoma. Neuro-Oncology. 20(1). 78–91. 35 indexed citations

16.

Wang, Yu, Shaofang Wu, Siyuan Zheng, et al.. (2017). APOBEC3G acts as a therapeutic target in mesenchymal gliomas by sensitizing cells to radiation-induced cell death. Oncotarget. 8(33). 54285–54296. 14 indexed citations

17.

Wu, Shaofang, Shuzhen Wang, Siyuan Zheng, et al.. (2016). MSK1-Mediated β-Catenin Phosphorylation Confers Resistance to PI3K/mTOR Inhibitors in Glioblastoma. Molecular Cancer Therapeutics. 15(7). 1656–1668. 25 indexed citations

18.

Wei, Xi, Shaofang Wu, Tanjing Song, et al.. (2016). Secondary interaction between MDMX and p53 core domain inhibits p53 DNA binding. Proceedings of the National Academy of Sciences. 113(19). E2558–63. 42 indexed citations

19.

Wu, Shaofang, Siyuan Zheng, Shuzhen Wang, W.K. Alfred Yung, & Dimpy Koul. (2015). Abstract 31: WEE1 kinase inhibition enhances PI3K inhibitor response in p53 deficient gliomas. Cancer Research. 75(15_Supplement). 31–31. 1 indexed citations

20.

Chen, Lihong, Wade M. Borcherds, Shaofang Wu, et al.. (2015). Autoinhibition of MDMX by intramolecular p53 mimicry. Proceedings of the National Academy of Sciences. 112(15). 4624–4629. 41 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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