Ping Wu

3.6k total citations · 1 hit paper
108 papers, 2.7k citations indexed

About

Ping Wu is a scholar working on Molecular Biology, Hematology and Oncology. According to data from OpenAlex, Ping Wu has authored 108 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Molecular Biology, 24 papers in Hematology and 19 papers in Oncology. Recurrent topics in Ping Wu's work include Multiple Myeloma Research and Treatments (20 papers), MicroRNA in disease regulation (12 papers) and Bone health and treatments (9 papers). Ping Wu is often cited by papers focused on Multiple Myeloma Research and Treatments (20 papers), MicroRNA in disease regulation (12 papers) and Bone health and treatments (9 papers). Ping Wu collaborates with scholars based in China, United Kingdom and Hong Kong. Ping Wu's co-authors include Fang Yang, Wei Wu, Danling Sun, Dexing Zhang, Yikai Zhou, Gareth J. Morgan, Faith E. Davies, Wuying Chu, Ching‐Lung Lai and Jianshe Zhang and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and Journal of Neuroscience.

In The Last Decade

Ping Wu

100 papers receiving 2.7k citations

Hit Papers

Assessment of heavy metal pollution and human health risk... 2018 2026 2020 2023 2018 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ping Wu China 28 999 493 433 290 276 108 2.7k
Liping Hu China 26 1.1k 1.1× 226 0.5× 261 0.6× 171 0.6× 198 0.7× 105 2.5k
Hiroshi Yamauchi Japan 33 1.2k 1.2× 190 0.4× 548 1.3× 276 1.0× 189 0.7× 158 4.0k
Dongmei Wu China 37 2.0k 2.0× 224 0.5× 247 0.6× 474 1.6× 448 1.6× 130 4.0k
Chen Zhao China 33 2.5k 2.5× 388 0.8× 901 2.1× 287 1.0× 679 2.5× 96 4.7k
Yanling Wang China 35 1.9k 1.9× 82 0.2× 509 1.2× 160 0.6× 642 2.3× 142 3.1k
Juan Zhang China 36 2.1k 2.1× 110 0.2× 305 0.7× 306 1.1× 833 3.0× 218 4.8k
Xiao Xiao China 32 1.7k 1.7× 58 0.1× 435 1.0× 397 1.4× 479 1.7× 140 3.7k
Georg Damm Germany 29 1.2k 1.2× 75 0.2× 292 0.7× 528 1.8× 224 0.8× 68 2.7k
Ziru Li United States 34 894 0.9× 204 0.4× 113 0.3× 606 2.1× 133 0.5× 101 3.4k
Daniele Tibullo Italy 37 1.8k 1.8× 593 1.2× 527 1.2× 213 0.7× 342 1.2× 182 3.9k

Countries citing papers authored by Ping Wu

Since Specialization
Citations

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

Fields of papers citing papers by Ping Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ping Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Ping Wu. A scholar is included among the top collaborators of Ping 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 Ping Wu. Ping 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
2.
Dong, Jianxia, Shan Ren, Ping Wu, et al.. (2025). Machine learning prediction of rapid HBsAg seroclearance at week 24 in inactive carriers treated with pegylated interferon. Hepatology International. 19(6). 1331–1346.
3.
Gu, Dangen, Zhen Zhou, Chenchen Zhu, et al.. (2025). Size-dependent and tissue specific accumulation of polystyrene microplastics and nanoplastics in zebrafish. Aquatic Toxicology. 291. 107678–107678.
4.
Wu, Wei, Zihao Wang, Wenwen Yang, et al.. (2025). Association between prenatal phthalate exposure and preschoolers’ blood pressure: Mediating role of DNA methylation in hypertension-related genes. Environmental Pollution. 390. 127450–127450.
5.
Li, Juanjuan, Cheng Peng, Li Wan, et al.. (2024). Metal Ruthenium Complexes Treat Spinal Cord Injury By Alleviating Oxidative Stress Through Interaction With Antioxidant 1 Copper Chaperone Protein. Advanced Science. 11(45). e2407225–e2407225. 4 indexed citations
6.
Chen, Tianjun, Li Wan, Yongjun Xiao, et al.. (2024). Curcumin/pEGCG-encapsulated nanoparticles enhance spinal cord injury recovery by regulating CD74 to alleviate oxidative stress and inflammation. Journal of Nanobiotechnology. 22(1). 653–653. 15 indexed citations
7.
Zhang, Yu, Ya‐Xiong Pan, Ping Wu, et al.. (2023). Exposure to waterborne cadmium induce disorder of lipid metabolism, antioxidant system and autophagy in the muscle of crayfish Procambarus clarkii. Aquaculture Reports. 29. 101497–101497. 9 indexed citations
9.
Zhu, Xinxia, Jingjie Liu, Ya‐Xiong Pan, et al.. (2022). The circadian rhythm regulates branched-chain amino acids metabolism in fast muscle of Chinese perch (Siniperca chuatsi) during short-term fasting by Clock-KLF15-Bcat2 pathway. British Journal Of Nutrition. 130(4). 604–615. 1 indexed citations
10.
Chen, Yuan‐Hua, Honghui Li, Jianshe Zhang, et al.. (2019). Dietary Ginkgo biloba leaf extract alters immune-related gene expression and disease resistance to Aeromonas hydrophila in common carp Cyprinus carpio. Fish & Shellfish Immunology. 94. 810–818. 39 indexed citations
11.
Wu, Ping, Jia Cheng, Lin Chen, et al.. (2018). Molecular Characterization, Spatial–Temporal Expression Profiles, and Injury‐responsive Regulation of Myocyte‐specific Enhancer Factor 2 Gene Family in the Ricefield Eel, Monopterus albus. Journal of the World Aquaculture Society. 49(2). 396–411. 1 indexed citations
12.
Wu, Wei, Ping Wu, Fang Yang, et al.. (2018). Association of phthalate exposure with anthropometric indices and blood pressure in first-grade children. Environmental Science and Pollution Research. 25(23). 23125–23134. 24 indexed citations
13.
Wu, Ping, Jia Cheng, Lin Chen, et al.. (2016). Transcriptome Analysis and Postprandial Expression of Amino Acid Transporter Genes in the Fast Muscles and Gut of Chinese Perch (Siniperca chuatsi). PLoS ONE. 11(7). e0159533–e0159533. 10 indexed citations
14.
Zhu, Xinxia, et al.. (2016). Molecular characterization and expression regulation of Smyd1a and Smyd1b in skeletal muscle of Chinese perch (Siniperca chuatsi). Comparative Biochemistry and Physiology Part B Biochemistry and Molecular Biology. 194-195. 25–31. 11 indexed citations
15.
Wu, Ping, Yu‐Long Li, Jia Cheng, et al.. (2016). Daily rhythmicity of clock gene transcript levels in fast and slow muscle fibers from Chinese perch (Siniperca chuatsi). BMC Genomics. 17(1). 1008–1008. 22 indexed citations
16.
Huang, Jian, Zhaomin Zhong, Mingyong Wang, et al.. (2015). Circadian Modulation of Dopamine Levels and Dopaminergic Neuron Development Contributes to Attention Deficiency and Hyperactive Behavior. Journal of Neuroscience. 35(6). 2572–2587. 109 indexed citations
17.
18.
Morgan, Gareth J., Graham Jackson, Faith E. Davies, et al.. (2012). Efficacy and side-effect profile of long-term bisphosphonate therapy in patients (pts) with multiple myeloma (MM): MRC myeloma IX study results.. Journal of Clinical Oncology. 30(15_suppl). 8015–8015. 1 indexed citations
19.
Lin, Borong, et al.. (2012). A Novel Effector Protein, MJ-NULG1a, Targeted to Giant Cell Nuclei Plays a Role inMeloidogyne javanicaParasitism. Molecular Plant-Microbe Interactions. 26(1). 55–66. 48 indexed citations
20.
Wu, Ping, Brian A. Walker, Daniel Brewer, et al.. (2011). A Gene Expression–Based Predictor for Myeloma Patients at High Risk of Developing Bone Disease on Bisphosphonate Treatment. Clinical Cancer Research. 17(19). 6347–6355. 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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