Chen Fu

2.4k citations
79 papers · 1.9k · 1 hit paper · h-index 24

Impact in

Papers in

Chen Fu

77 papers receiving 1.9k citations

Chen Fu's Hit Papers

The future of pharmaceuticals: Artificial intelligence in drug discovery and development 2025 · 41 citations
410Years since publication10203040

Peers

Chen Fu
Comparison fields: 5 of 120
  • Oncology 443
  • Inorganic Chemistry 204
  • Organic Chemistry 399
  • Pathology and Forensic Medicine 180
  • Biomaterials 147
Replace Ga Young Park with:
Ga Young Park South Korea
Lixia Wang China
Chunyu Zhang China
Donato Colangelo Italy
Haeri Lee South Korea
Yugang Liu China
Qin Yang China
B Desoize France
David Bauer United States
Ran Li China
Chen Fu relative to Ga Young Park South Korea Ga Young Park's profile →
Citations per field
00.5×3.2×
Ga Young Park · 1×
Citations per year

Countries citing papers authored by Chen Fu

Since Specialization
Citations

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

Fields of papers citing papers by Chen Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Clonability and tumorigenicity of human epithelial cells expressing the EBV encoded membrane protein LMP1.
1993170
2 2017167
3 2014161
4 199876
5 201976
6 201974
7 202073
8 201761
9 202159
10 202053
11 201452
12 199644
13 201844
14 201443
15 202142
16 201741
17
The future of pharmaceuticals: Artificial intelligence in drug discovery and development
Hit paper breakdown →
202541
18 201840
19 201837
20 201736

About Chen Fu

Chen Fu is a scholar working on Molecular Biology, Organic Chemistry, Oncology, Inorganic Chemistry and Materials Chemistry, having authored 79 papers that have together received 1.9k indexed citations. Recurring topics across this work include Metal complexes synthesis and properties (9 papers), Asymmetric Hydrogenation and Catalysis (7 papers), Viral-associated cancers and disorders (7 papers), Advanced biosensing and bioanalysis techniques (6 papers), Parvovirus B19 Infection Studies (5 papers), Nanocluster Synthesis and Applications (5 papers), Cytomegalovirus and herpesvirus research (4 papers) and Organometallic Complex Synthesis and Catalysis (4 papers). The work is most often cited by research in Oncology (443 citations), Inorganic Chemistry (204 citations), Organic Chemistry (399 citations), Pathology and Forensic Medicine (180 citations) and Biomaterials (147 citations). Chen Fu has collaborated with scholars based in China, Germany and Sweden. Frequent co-authors include Ailing Fu, Eric Meggers, Klaus Harms, Haohua Huo, Ming Zhao, George Klein, Li–Fu Hu, Gösta Winberg, Qi Chen and Ingemar Ernberg. Their work appears in journals such as Chemical Communications, Inorganic Chemistry, Materials Science and Engineering C, International Journal of Cancer and European Journal of Inorganic Chemistry.

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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