Penggao Dai

1.2k total citations
48 papers, 944 citations indexed

About

Penggao Dai is a scholar working on Molecular Biology, Pharmacology and Immunology. According to data from OpenAlex, Penggao Dai has authored 48 papers receiving a total of 944 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 8 papers in Pharmacology and 8 papers in Immunology. Recurrent topics in Penggao Dai's work include Computational Drug Discovery Methods (4 papers), Carbon and Quantum Dots Applications (4 papers) and Luminescence and Fluorescent Materials (4 papers). Penggao Dai is often cited by papers focused on Computational Drug Discovery Methods (4 papers), Carbon and Quantum Dots Applications (4 papers) and Luminescence and Fluorescent Materials (4 papers). Penggao Dai collaborates with scholars based in China, United States and Canada. Penggao Dai's co-authors include Lin Mei, Wen‐Cheng Xiong, Yannan Ouyang, Jianxin Bao, Tae‐Wan Kim, Kevin K. Ohlemiller, Hana Lin, Richard T. Ambron, Abdullah A. Osman and Debin Lei and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Neuroscience.

In The Last Decade

Penggao Dai

47 papers receiving 935 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Penggao Dai China 18 561 139 132 106 92 48 944
Eileen J. Kennedy United States 19 894 1.6× 123 0.9× 157 1.2× 69 0.7× 110 1.2× 55 1.2k
Motoko Ohnishi Japan 17 899 1.6× 120 0.9× 160 1.2× 117 1.1× 102 1.1× 42 1.2k
Sukalyan Chatterjee United States 16 643 1.1× 126 0.9× 80 0.6× 111 1.0× 73 0.8× 19 956
Chung-Ming Lin Taiwan 13 532 0.9× 133 1.0× 150 1.1× 71 0.7× 65 0.7× 23 992
Jaganmohan R. Jangamreddy Sweden 13 698 1.2× 189 1.4× 155 1.2× 150 1.4× 147 1.6× 20 1.4k
Shaosong Yang United States 12 745 1.3× 98 0.7× 174 1.3× 85 0.8× 56 0.6× 13 1.1k
Jian Xiong China 20 464 0.8× 81 0.6× 112 0.8× 148 1.4× 62 0.7× 69 1.1k
Won Hee Jang South Korea 17 465 0.8× 86 0.6× 66 0.5× 83 0.8× 123 1.3× 42 1.1k
Ha‐Na Woo South Korea 18 830 1.5× 100 0.7× 180 1.4× 130 1.2× 175 1.9× 38 1.5k
Samy A.F. Morad Egypt 18 904 1.6× 145 1.0× 176 1.3× 144 1.4× 63 0.7× 33 1.2k

Countries citing papers authored by Penggao Dai

Since Specialization
Citations

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

Fields of papers citing papers by Penggao Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Penggao Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Penggao Dai. A scholar is included among the top collaborators of Penggao Dai 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 Penggao Dai. Penggao Dai 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.
Jiao, Wangbo, Jia Li, Zhenli He, et al.. (2025). Intracellular Magnetic Nanodelivery of H 2 S and Heat Synergize to Reshape the Tumor Immune Microenvironment. Advanced Healthcare Materials. 14(23). e2501617–e2501617. 1 indexed citations
2.
Jie, Yanni, Yang Gao, Ge Yang, et al.. (2023). Yellow-Emissive Carbon Dots with Long-Lifetime Room-Temperature Phosphorescence for Information Encryption and Bioimaging. ACS Applied Nano Materials. 6(21). 20431–20439. 12 indexed citations
3.
Dai, Penggao, Wenjing Zhu, Bin Yan, et al.. (2021). Regulation of ID4 In Vivo for Efficient Magnetothermal Therapy of Breast Cancer. Advanced Therapeutics. 4(5). 7 indexed citations
4.
Ma, Jun, et al.. (2019). Network-based approach to identify principal isoforms among four cancer types. Molecular Omics. 15(2). 117–129. 6 indexed citations
5.
6.
Wang, Le, Hao Wang, Xianglong Duan, Penggao Dai, & Jianping Li. (2019). Comprehensive Analysis of the Canonical and Non-canonical Wnt Signaling Pathways in Gastric Cancer. Digestive Diseases and Sciences. 64(10). 2830–2842. 8 indexed citations
7.
Ma, Jun, et al.. (2019). A Comparative Study of Cluster Detection Algorithms in Protein–Protein Interaction for Drug Target Discovery and Drug Repurposing. Frontiers in Pharmacology. 10. 109–109. 29 indexed citations
8.
Zhang, Jiayi, Huijuan Wang, Yongkang Liu, et al.. (2018). Deciphering DMET genetic data: comprehensive assessment of Northwestern Han, Tibetan, Uyghur populations and their comparison to eleven 1000 genome populations. Artificial Cells Nanomedicine and Biotechnology. 46(sup3). 1176–1185. 2 indexed citations
9.
10.
Pang, Cong, et al.. (2015). The allele frequency of CYP2A6*4 in four ethnic groups of China. Experimental and Molecular Pathology. 98(3). 546–548. 6 indexed citations
11.
Wang, Ting, Jinhui Liu, Jie Zhang, et al.. (2015). A multiplex allele-specific real-time PCR assay for screening of ESR1 mutations in metastatic breast cancer. Experimental and Molecular Pathology. 98(2). 152–157. 12 indexed citations
12.
Wang, Huijuan, et al.. (2014). Tissue-specific selection of optimal reference genes for expression analysis of anti-cancer drug-related genes in tumor samples using quantitative real-time RT-PCR. Experimental and Molecular Pathology. 98(3). 375–381. 22 indexed citations
13.
Xie, Ling, Cui Liu, Li Wang, et al.. (2013). Protein Phosphatase 2A Catalytic Subunit α Plays a MyD88-Dependent, Central Role in the Gene-Specific Regulation of Endotoxin Tolerance. Cell Reports. 3(3). 678–688. 30 indexed citations
14.
Zhu, Hongli, Penggao Dai, Chao Luo, et al.. (2011). Pharmacodynamic Study of Polymerized Porcine Hemoglobin (pPolyHb) in a Rat Model of Exchange Transfusion. Artificial Cells Blood Substitutes and Biotechnology. 39(3). 119–126. 13 indexed citations
15.
Zhang, Wei, et al.. (2011). A Novel Hemoglobin‐Based Oxygen Carrier, Polymerized Porcine Hemoglobin, Inhibits H2O2‐Induced Cytotoxicity of Endothelial Cells. Artificial Organs. 36(2). 151–160. 17 indexed citations
16.
Tao, Yanmei, Penggao Dai, Yu Liu, et al.. (2009). Erbin regulates NRG1 signaling and myelination. Proceedings of the National Academy of Sciences. 106(23). 9477–9482. 62 indexed citations
17.
Dai, Penggao, Sun Yong Jeong, Yanbao Yu, et al.. (2009). Modulation of TLR Signaling by Multiple MyD88-Interacting Partners Including Leucine-Rich Repeat Fli-I-Interacting Proteins. The Journal of Immunology. 182(6). 3450–3460. 70 indexed citations
18.
Dai, Fangyan, Chenbei Chang, Xia Lin, et al.. (2007). Erbin Inhibits Transforming Growth Factor β Signaling through a Novel Smad-Interacting Domain. Molecular and Cellular Biology. 27(17). 6183–6194. 49 indexed citations
19.
Dai, Penggao, Robert P. Borris, Anne W. Dombrowski, et al.. (1994). A new indole from Penicillium daleae.. The Journal of Antibiotics. 47(6). 724–726. 6 indexed citations
20.
Dai, Penggao, et al.. (1994). Isolation and identification of a novel microbial alkaloid.. The Journal of Antibiotics. 47(1). 110–112. 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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