Wang Fen

35 papers receiving 731 citations

Peers

Wang Fen
Comparison fields: 5 of 110
  • Hepatology 109
  • Sensory Systems 47
  • Endocrine and Autonomic Systems 42
  • Pharmacology 37
  • Oncology 114
Replace Hennie Bikker with:
Hennie Bikker Netherlands
Natalia O. Glebova United States
Yumi Noda Japan
Marco M. Hefti United States
Norman Fleischer United States
Marina T. DiStefano United States
Fredrik Holmquist Sweden
Cheryl E. Gariepy United States
Arye Lev-Ran United States
Kai Wei China
Wang Fen relative to Hennie Bikker Netherlands Hennie Bikker's profile →
Citations per field
00.5×3.5×
Hennie Bikker · 1×
Citations per year

Countries citing papers authored by Wang Fen

Since Specialization
Citations

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

Fields of papers citing papers by Wang Fen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003136
2 2002107
3 201866
4 200164
5 201554
6 200554
7 201128
8 201522
9 201821
10 200919
11 201718
12
Integrated interventions for improving negative emotions and stress reactions of young women receiving total hysterectomy.
201418
13 202116
14 201614
15 201012
16 202111
17 201711
18 201810
19 202010
20 20209

About Wang Fen

Wang Fen is a scholar working on Molecular Biology, Surgery, Pulmonary and Respiratory Medicine, Physiology and Pharmacology, having authored 39 papers that have together received 743 indexed citations. Recurring topics across this work include Parkinson's Disease Mechanisms and Treatments (3 papers), Fibroblast Growth Factor Research (3 papers), Biochemical Analysis and Sensing Techniques (2 papers), Anesthesia and Neurotoxicity Research (2 papers), Receptor Mechanisms and Signaling (2 papers), Atherosclerosis and Cardiovascular Diseases (2 papers), Sleep and related disorders (2 papers) and Fungal Biology and Applications (2 papers). The work is most often cited by research in Hepatology (109 citations), Sensory Systems (47 citations), Endocrine and Autonomic Systems (42 citations), Pharmacology (37 citations) and Oncology (114 citations). Wang Fen has collaborated with scholars based in China, United States and Mexico. Frequent co-authors include Chundong Yu, Chengliu Jin, Wallace L. McKeehan, Mingyao Liu, Claudio Basilico, David L. Miller, Xinqiang Huang, Waikin Chan, Xiaochong Wu and Parvesh Kumar. Their work appears in journals such as American Journal Of Pathology, Parkinsonism & Related Disorders, Mycology: An International Journal on Fungal Biology, Behavioural Brain Research and BMC Anesthesiology.

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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