ZhengMing Wu

1.3k total citations · 1 hit paper
16 papers, 868 citations indexed

About

ZhengMing Wu is a scholar working on Molecular Biology, Cell Biology and Oncology. According to data from OpenAlex, ZhengMing Wu has authored 16 papers receiving a total of 868 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 7 papers in Cell Biology and 6 papers in Oncology. Recurrent topics in ZhengMing Wu's work include Hippo pathway signaling and YAP/TAZ (6 papers), CAR-T cell therapy research (4 papers) and Wnt/β-catenin signaling in development and cancer (4 papers). ZhengMing Wu is often cited by papers focused on Hippo pathway signaling and YAP/TAZ (6 papers), CAR-T cell therapy research (4 papers) and Wnt/β-catenin signaling in development and cancer (4 papers). ZhengMing Wu collaborates with scholars based in United States, China and Norway. ZhengMing Wu's co-authors include Kun‐Liang Guan, James Franklin, Qingquan Li, Karl‐Johan Malmberg, Eivind Heggernes Ask, Dan S. Kaufman, Zhu Huang, Robert Blum, Zhipeng Meng and Hanna Julie Hoel and has published in prestigious journals such as Nature, Nature Communications and Nature reviews. Cancer.

In The Last Decade

ZhengMing Wu

15 papers receiving 859 citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Insights into recent findings and clinical application of YAP and TAZ in cancer

2023 120 citations James Franklin, ZhengMing Wu et al. Nature reviews. Cancer profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
ZhengMing Wu United States	9	469	304	274	235	144	16	868
Cheryl McFarlane United Kingdom	14	460 1.0×	246 0.8×	132 0.5×	102 0.4×	128 0.9×	19	680
Yee Mon Thu United States	11	485 1.0×	459 1.5×	92 0.3×	344 1.5×	197 1.4×	16	954
María José Sandí France	13	462 1.0×	183 0.6×	166 0.6×	118 0.5×	127 0.9×	21	738
Dmytro Starenki United States	16	458 1.0×	235 0.8×	89 0.3×	102 0.4×	140 1.0×	28	702
Thomas W. Owens United Kingdom	14	542 1.2×	199 0.7×	93 0.3×	97 0.4×	98 0.7×	18	742
Shikha Sharan United States	12	409 0.9×	225 0.7×	78 0.3×	136 0.6×	149 1.0×	16	665
Vanessa Ott United States	13	342 0.7×	155 0.5×	237 0.9×	498 2.1×	73 0.5×	17	1.1k
Weei-Chin Lin United States	12	517 1.1×	243 0.8×	121 0.4×	176 0.7×	96 0.7×	12	716
Ryo Koyama‐Nasu Japan	17	659 1.4×	237 0.8×	62 0.2×	213 0.9×	170 1.2×	30	972
Antony Letai United States	11	545 1.2×	303 1.0×	81 0.3×	104 0.4×	163 1.1×	11	840

Countries citing papers authored by ZhengMing Wu

Since Specialization

Citations

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

Fields of papers citing papers by ZhengMing Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of ZhengMing Wu

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

All Works

Sort: Min cites: Since: Top N: Style:

16 of 16 papers shown

Huang, Yawen, Qianchun Deng, ZhengMing Wu, et al.. (2025). Enzymatic modification of oilseed proteins for improved functional properties. Trends in Food Science & Technology. 167. 105443–105443.

Franklin, James, ZhengMing Wu, & Kun‐Liang Guan. (2023). Insights into recent findings and clinical application of YAP and TAZ in cancer. Nature reviews. Cancer. 23(8). 512–525. 120 indexed citations breakdown →

Wu, ZhengMing, et al.. (2023). YAP silencing by RB1 mutation is essential for small-cell lung cancer metastasis. Nature Communications. 14(1). 5916–5916. 36 indexed citations

Li, Zhaoning, ZhengMing Wu, Anqi Liu, et al.. (2023). Towards Human-Compatible Autonomous Car: A Study of Non-Verbal Turing Test in Automated Driving With Affective Transition Modelling. IEEE Transactions on Affective Computing. 15(2). 478–492. 3 indexed citations

Li, Fulong, Vivian Fu, Guangbo Liu, et al.. (2022). Hippo pathway regulation by phosphatidylinositol transfer protein and phosphoinositides. Nature Chemical Biology. 18(10). 1076–1086. 41 indexed citations

Xu, Chenyue, Qiongmei Gao, ZhengMing Wu, et al.. (2022). Combined HASPIN and mTOR inhibition is synergistic against KRAS-driven carcinomas. Translational Oncology. 26. 101540–101540. 1 indexed citations

Li, Xiaoyan, ZhengMing Wu, Jing He, et al.. (2021). OGT regulated O-GlcNAcylation promotes papillary thyroid cancer malignancy via activating YAP. Oncogene. 40(30). 4859–4871. 46 indexed citations

Ma, Shenghong, ZhengMing Wu, Feng Yang, et al.. (2021). Hippo signalling maintains ER expression and ER+ breast cancer growth. Nature. 591(7848). E1–E10. 51 indexed citations

Huang, Zhu, Robert Blum, Davide Bernareggi, et al.. (2020). Metabolic Reprograming via Deletion of CISH in Human iPSC-Derived NK Cells Promotes In Vivo Persistence and Enhances Anti-tumor Activity. Cell stem cell. 27(2). 224–237.e6. 233 indexed citations

10.

Wu, ZhengMing & Kun‐Liang Guan. (2020). Hippo Signaling in Embryogenesis and Development. Trends in Biochemical Sciences. 46(1). 51–63. 159 indexed citations

11.

Huang, Zhu, Robert Blum, Davide Bernareggi, et al.. (2020). Metabolic Reprograming Due to Deletion of <i>CISH</i> in Human Natural Killer Cells Promotes <i>in vivo</i> Persistence and Enhances Anti-Tumor Activity. SSRN Electronic Journal. 1 indexed citations

12.

Huang, Zhu, Robert Blum, ZhengMing Wu, et al.. (2019). Deletion of CISH in Human Pluripotent Stem Cell-Derived Natural Killer Cells Enhances Anti-Tumor Activity Via Metabolic Reprogramming. Blood. 134(Supplement_1). 619–619. 4 indexed citations

13.

Du, Zunguo, Xiujuan Liu, Tao Chen, et al.. (2018). Targeting a Sirt5-Positive Subpopulation Overcomes Multidrug Resistance in Wild-Type Kras Colorectal Carcinomas. Cell Reports. 22(10). 2677–2689. 44 indexed citations

14.

Huang, Zhu, Robert Blum, ZhengMing Wu, et al.. (2018). Notch Activation Rescues Exhaustion in CISH-Deleted Human iPSC-Derived Natural Killer Cells to Promote In Vivo Persistence and Enhance Anti-Tumor Activity. Blood. 132(Supplement 1). 1279–1279. 3 indexed citations

15.

Wu, ZhengMing, Wenchao Gao, Zhiqian Hu, et al.. (2015). TPO-Induced Metabolic Reprogramming Drives Liver Metastasis of Colorectal Cancer CD110+ Tumor-Initiating Cells. Cell stem cell. 17(1). 47–59. 124 indexed citations

16.

Wu, ZhengMing. (2003). Studies on anticancer activities of triterpenoid in Anemone raddeana Regel. Chinese New Drugs Journal. 2 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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