Fan Li

3.6k citations
94 papers · 2.7k indexed · 1 hit paper · h-index 27
Topics
Advanced biosensing and bioanalysis techniques (41 papers)RNA Interference and Gene Delivery (21 papers)DNA and Nucleic Acid Chemistry (11 papers)
Partner nations
ChinaUnited StatesIndia

In The Last Decade

Fan Li

92 papers receiving 2.7k citations

Hit Papers

A multi-model deep convolutional neural network for autom...20192026202120232019100200300

Peers

Fan Li
Comparison fields: 5 of 151
  • Molecular Biology 1.7k
  • Biomedical Engineering 695
  • Materials Chemistry 398
  • Neurology 270
  • Electronic, Optical and Magnetic Materials 207
Replace Wenjin Li with:
Wenjin Li China
Yan Chen China
Madhavan Nair United States
Jianmei Gao China
Xinwei Li China
Hongzhi Wang China
Yun‐Sang Lee South Korea
Xiaoyan Xiao China
Yibo Wang China
Furong Huang China
Fan Li relative to Wenjin Li China Wenjin Li's profile →
Citations per field
00.5×3.0×
Wenjin Li · 1×
Citations per year

Countries citing papers authored by Fan Li

Since Specialization
Citations

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

Fields of papers citing papers by Fan Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fan Li

This figure shows the co-authorship network connecting the top 25 collaborators of Fan Li. A scholar is included among the top collaborators of Fan Li 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 Fan Li. Fan Li 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
#WorkIndexed citations
1 6
2 1
3 1
4 6
5 1
6 3
7 8
8 4
9 2
10 2
11 94
12 7
13 57
14 6
15 43
16 41
17 78
18
A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer’s diseasebreakdown →
366
19 17
20 15

About Fan Li

Fan Li is a scholar working on Molecular Biology, Neurology and Electrochemistry, having authored 94 papers that have together received 2.7k indexed citations. Recurring topics across this work include Advanced biosensing and bioanalysis techniques (41 papers), RNA Interference and Gene Delivery (21 papers) and DNA and Nucleic Acid Chemistry (11 papers). The work is most often cited by research in Neurology (270 citations), Molecular Biology (1.7k citations) and Biomedical Engineering (695 citations). Fan Li has collaborated with scholars based in China, United States and India. Frequent co-authors include Chunhai Fan, Xiaolei Zuo, Xiuhai Mao, Min Li, Manhua Liu, Yixin Ma, Hao Yan, Li Shen, Kundong Wang and Fangfei Yin. Their work appears in journals such as Chemical Reviews, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

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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