Gan Dai

1.2k total citations · 1 hit paper
15 papers, 878 citations indexed

About

Gan Dai is a scholar working on Molecular Biology, Cancer Research and Immunology. According to data from OpenAlex, Gan Dai has authored 15 papers receiving a total of 878 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 5 papers in Cancer Research and 4 papers in Immunology. Recurrent topics in Gan Dai's work include Glioma Diagnosis and Treatment (3 papers), Antimicrobial Peptides and Activities (3 papers) and Cancer-related molecular mechanisms research (3 papers). Gan Dai is often cited by papers focused on Glioma Diagnosis and Treatment (3 papers), Antimicrobial Peptides and Activities (3 papers) and Cancer-related molecular mechanisms research (3 papers). Gan Dai collaborates with scholars based in China and United States. Gan Dai's co-authors include Linqian Wang, Liyu Chen, Yapeng Zhang, Guojun Wu, Feizhou Zhu, Qianqian Liu, Zhongyi Cheng, Weiyu Jiang, Mallika Achanta and Yugendar R. Bommineni and has published in prestigious journals such as PLoS ONE, Journal of Proteome Research and Experimental Biology and Medicine.

In The Last Decade

Gan Dai

14 papers receiving 865 citations

Hit Papers

align trajectories

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.

Antibacterial activity and mechanism of silver nanoparticles against multidrug-resistant Pseudomonas aeruginosa

2019 372 citations Yapeng Zhang, Feizhou Zhu et al. International Journal of Nanomedicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gan Dai China	9	321	265	164	140	116	15	878
Maozhi Hu China	19	257 0.8×	216 0.8×	109 0.7×	54 0.4×	33 0.3×	50	1.2k
Zhixin Lei China	16	312 1.0×	69 0.3×	208 1.3×	49 0.3×	108 0.9×	50	917
Yinyan Yin China	18	228 0.7×	109 0.4×	66 0.4×	94 0.7×	86 0.7×	36	750
Seyed Ali Mirhosseini Iran	18	496 1.5×	136 0.5×	149 0.9×	32 0.2×	327 2.8×	50	1.1k
Rashmirekha Pati India	9	340 1.1×	297 1.1×	156 1.0×	19 0.1×	87 0.8×	14	1.0k
Seung Won Shin South Korea	18	325 1.0×	248 0.9×	235 1.4×	20 0.1×	44 0.4×	66	1.1k
Calvin T. Sung United States	20	615 1.9×	65 0.2×	116 0.7×	41 0.3×	141 1.2×	49	1.5k
Sufen Li China	19	270 0.8×	70 0.3×	159 1.0×	413 3.0×	21 0.2×	82	1.1k
Shuai Su China	16	234 0.7×	133 0.5×	56 0.3×	100 0.7×	11 0.1×	61	915

Countries citing papers authored by Gan Dai

Since Specialization

Citations

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

Fields of papers citing papers by Gan Dai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gan Dai

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

All Works

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15 of 15 papers shown

Xu, Shengchao, Xi Yan, Gan Dai, & Chengke Luo. (2021). A Novel Mice Model for Studying the Efficacy and IRAEs of Anti-CTLA4 Targeted Immunotherapy. Frontiers in Oncology. 11. 692403–692403. 4 indexed citations

Xu, Shengchao, Lu Tang, Gan Dai, Chengke Luo, & Zhixiong Liu. (2021). Immune-related genes with APA in microenvironment indicate risk stratification and clinical prognosis in grade II/III gliomas. Molecular Therapy — Nucleic Acids. 23. 1229–1242. 19 indexed citations

Luo, Chengke, Shengchao Xu, Gan Dai, et al.. (2020). Tumor treating fields for high-grade gliomas. Biomedicine & Pharmacotherapy. 127. 110193–110193. 29 indexed citations

Xu, Shengchao, Lu Tang, Gan Dai, Chengke Luo, & Zhixiong Liu. (2020). Expression of m6A Regulators Correlated With Immune Microenvironment Predicts Therapeutic Efficacy and Prognosis in Gliomas. Frontiers in Cell and Developmental Biology. 8. 594112–594112. 59 indexed citations

Zhang, Yapeng, Linqian Wang, Yurong Tang, et al.. (2020). Quantitative Proteomics Reveals the Mechanism of Silver Nanoparticles against Multidrug-Resistant Pseudomonas aeruginosa Biofilms. Journal of Proteome Research. 19(8). 3109–3122. 64 indexed citations

Zhang, Yapeng, Feizhou Zhu, Qianqian Liu, et al.. (2019). Antibacterial activity and mechanism of silver nanoparticles against multidrug-resistant Pseudomonas aeruginosa. International Journal of Nanomedicine. Volume 14. 1469–1487. 372 indexed citations breakdown →

Chen, Guo, Rona S. Scott, Yonglin Chen, et al.. (2019). Prevalence and characteristics of Epstein‐Barr virus associated gastric carcinoma in Gansu Province, Northwest China with mRNA expression of glycoprotein BMRF2. Journal of Medical Virology. 92(3). 356–363. 6 indexed citations

Shi, Ke, Xi Chen, Bin Xie, et al.. (2018). Celastrol Alleviates Chronic Obstructive Pulmonary Disease by Inhibiting Cellular Inflammation Induced by Cigarette Smoke via the Ednrb/Kng1 Signaling Pathway. Frontiers in Pharmacology. 9. 1276–1276. 34 indexed citations

Wang, Linqian, et al.. (2017). Hsa-miR-27b is up-regulated in cytomegalovirus-infected human glioma cells, targets engrailed-2 and inhibits its expression. Experimental Biology and Medicine. 242(12). 1227–1233. 11 indexed citations

10.

Dai, Gan. (2015). Societal metabolism analysis of China's four municipalities based on MSIASM theory and carbon emissions from energy consumption. 1 indexed citations

11.

Achanta, Mallika, Lakshmi T. Sunkara, Gan Dai, et al.. (2012). Tissue expression and developmental regulation of chicken cathelicidin antimicrobial peptides. Journal of Animal Science and Biotechnology. 3(1). 15–15. 49 indexed citations

12.

Sunkara, Lakshmi T., Mallika Achanta, Nicole B. Schreiber, et al.. (2011). Butyrate Enhances Disease Resistance of Chickens by Inducing Antimicrobial Host Defense Peptide Gene Expression. PLoS ONE. 6(11). e27225–e27225. 215 indexed citations

13.

Wang, Shiping, et al.. (2007). Cloning, expression and protective immunity evaluation of the full-length cDNA encoding succinate dehydrogenase iron-sulfur protein of Schistosoma japonicum. Science in China Series C Life Sciences. 50(2). 221–227. 8 indexed citations

14.

Dai, Gan, et al.. (2007). Vaccination against <italic>Schistosoma japonicum</italic> Infection by DNA Vaccine Encoding Sj22.7 Antigen. Acta Biochimica et Biophysica Sinica. 39(1). 27–36. 7 indexed citations

15.

Xie, Ni, Liyu Chen, & Gan Dai. (2003). [Experimental study of mouse infected with human cytomegalovirus AD169 strain].. PubMed. 28(3). 243–6.

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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