Yuedi Ding

1.5k citations
44 papers · 1.3k · h-index 21

Impact in

    • Advanced biosensing and bioanalysis techniques
    • CRISPR and Genetic Engineering
    • Extracellular vesicles in disease
    • RNA Interference and Gene Delivery
    • SARS-CoV-2 detection and testing

Papers in

    • Advanced biosensing and bioanalysis techniques 16
    • RNA Interference and Gene Delivery 4
    • CRISPR and Genetic Engineering 4
    • Virus-based gene therapy research 9

Yuedi Ding

43 papers receiving 1.2k citations

Peers

Yuedi Ding
Comparison fields: 5 of 92
  • Molecular Biology 915
  • Infectious Diseases 229
  • Cancer Research 174
  • Biomedical Engineering 312
  • Electrochemistry 42
Replace Jun Fan with:
Jun Fan China
Samuele Raccosta Italy
Xibao Zhang China
Hua Pei China
Kanokwan Sansanaphongpricha Thailand
Lihua Ding China
P. Scott Pine United States
Sukanta S. Bhattacharya United States
Shuaijian Ni China
Mohamed Wehbe Canada
Yuedi Ding relative to Jun Fan China Jun Fan's profile →
Citations per field
00.5×5.3×
Jun Fan · 1×
Citations per year

Countries citing papers authored by Yuedi Ding

Since Specialization
Citations

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

Fields of papers citing papers by Yuedi Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yuedi Ding, 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 Yuedi Ding Line = papers co-authored together Yuedi Ding links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015172
2 2021130
3 202187
4 202184
5 202174
6 202174
7 202170
8 201447
9 201737
10 201733
11 202032
12 201731
13 201429
14 202125
15 202123
16 201623
17 202123
18 202022
19 202122
20 202022

About Yuedi Ding

Yuedi Ding is a scholar working on Molecular Biology, Genetics, Infectious Diseases, Oncology and Biomedical Engineering, having authored 44 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced biosensing and bioanalysis techniques (16 papers), Virus-based gene therapy research (9 papers), SARS-CoV-2 detection and testing (7 papers), Biosensors and Analytical Detection (6 papers), RNA Interference and Gene Delivery (4 papers), Cancer Research and Treatments (4 papers), CRISPR and Genetic Engineering (4 papers) and SARS-CoV-2 and COVID-19 Research (3 papers). The work is most often cited by research in Molecular Biology (915 citations), Infectious Diseases (229 citations), Cancer Research (174 citations), Biomedical Engineering (312 citations) and Electrochemistry (42 citations). Yuedi Ding has collaborated with scholars based in China, Fiji and Poland. Frequent co-authors include Zhenqiang Fan, Kai Zhang, Minhao Xie, Bo Yao, Lili Deng, Ying Peng, Yu‐Wei Wu, Jun Fan, Jing Zhao and Yaping Wang. Their work appears in journals such as Biosensors and Bioelectronics, The Journal of Steroid Biochemistry and Molecular Biology, Chemical Communications, Oncotarget and Talanta.

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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