Gan Dai

14 papers receiving 892 citations

Gan Dai's Hit Papers

<p>Antibacterial activity and mechanism of silver nanoparticles against multidrug-resistant <em>Pseudomonas aeruginosa</em></p> 2019 · 390 citations
3900+2+4Years since publication100200300

Peers

Gan Dai
Comparison fields: 5 of 107
  • Microbiology 113
  • Animal Science and Zoology 139
  • Food Science 107
  • Molecular Medicine 28
  • Materials Chemistry 268
Replace Calvin T. Sung with:
Calvin T. Sung United States
Rashmirekha Pati India
Yinyan Yin China
Hongmei Li China
Hsiao‐Wei Wen Taiwan
Zhixin Lei China
Ajay Kumar India
Seyed Ali Mirhosseini Iran
D. G. Deryabin Russia
Jianying Huang China
Gan Dai relative to Calvin T. Sung United States Calvin T. Sung's profile →
Citations per field
00.5×4.3×
Calvin T. Sung · 1×
Citations per year

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-authors

The 25 scholars most cited alongside Gan Dai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gan Dai Line = papers co-authored together Gan Dai links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1
<p>Antibacterial activity and mechanism of silver nanoparticles against multidrug-resistant <em>Pseudomonas aeruginosa</em></p>
Hit paper breakdown →
2019390
2 2011218
3 202066
4 202059
5 201249
6 201836
7 202030
8 202119
9 201711
10 20078
11 20077
12 20196
13 20214
14
Societal metabolism analysis of China's four municipalities based on MSIASM theory and carbon emissions from energy consumption
20151
15
[Experimental study of mouse infected with human cytomegalovirus AD169 strain].
20030

About Gan Dai

Gan Dai is a scholar working on Molecular Biology, Cancer Research, Microbiology, Immunology and Genetics, having authored 15 papers that have together received 904 indexed citations. Recurring topics across this work include Antimicrobial Peptides and Activities (3 papers), Parasites and Host Interactions (2 papers), Bacterial biofilms and quorum sensing (2 papers), Glioma Diagnosis and Treatment (2 papers), Cancer-related molecular mechanisms research (2 papers), Trypanosoma species research and implications (1 paper), Ferroptosis and cancer prognosis (1 paper) and Inflammation biomarkers and pathways (1 paper). The work is most often cited by research in Microbiology (113 citations), Animal Science and Zoology (139 citations), Food Science (107 citations), Molecular Medicine (28 citations) and Materials Chemistry (268 citations). Gan Dai has collaborated with scholars based in China and United States. Frequent co-authors include Linqian Wang, Liyu Chen, Yapeng Zhang, Xuanhe Pan, Guojun Wu, Zhongyi Cheng, Qianqian Liu, Feizhou Zhu, Yugendar R. Bommineni and Guolong Zhang. Their work appears in journals such as Experimental Biology and Medicine, PLoS ONE, Frontiers in Cell and Developmental Biology, International Journal of Nanomedicine and Acta Biochimica et Biophysica Sinica.

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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