Chenying Fu

2.3k citations
52 papers · 1.5k · 1 hit paper · h-index 19

Impact in

Papers in

Chenying Fu

50 papers receiving 1.5k citations

Chenying Fu's Hit Papers

Signaling pathways and targeted therapy for myocardial infarction 2022 · 551 citations
5510+1+2Years since publication100200300400500

Peers

Chenying Fu
Comparison fields: 5 of 120
  • Cardiology and Cardiovascular Medicine 231
  • Complementary and Manual Therapy 21
  • Cancer Research 131
  • Pathology and Forensic Medicine 149
  • Developmental Neuroscience 29
Replace Matteo Beretta with:
Matteo Beretta Italy
Stephen F. Rodrigues Brazil
Elisabetta Ferraro Italy
Daniela Galli Italy
Hualin Sun China
Shih‐Ping Liu Taiwan
Angela D’Ascola Italy
Amritlal Mandal United States
Chenying Fu relative to Matteo Beretta Italy Matteo Beretta's profile →
Citations per field
00.5×10×13.8×
Matteo Beretta · 1×
Citations per year

Countries citing papers authored by Chenying Fu

Since Specialization
Citations

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

Fields of papers citing papers by Chenying Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Signaling pathways and targeted therapy for myocardial infarction
Hit paper breakdown →
2022551
2 2021105
3 202083
4 202277
5 202377
6 202446
7 202132
8 202031
9 202130
10 202028
11 202327
12 202227
13 201924
14 202023
15 201820
16 202119
17 201919
18 201819
19 202218
20 201418

About Chenying Fu

Chenying Fu is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Cell Biology, Biophysics and Surgery, having authored 52 papers that have together received 1.5k indexed citations. Recurring topics across this work include Electromagnetic Fields and Biological Effects (6 papers), Spinal Cord Injury Research (4 papers), MicroRNA in disease regulation (4 papers), Signaling Pathways in Disease (3 papers), Cardiac Fibrosis and Remodeling (3 papers), Cancer-related molecular mechanisms research (3 papers), Circular RNAs in diseases (3 papers) and Caveolin-1 and cellular processes (3 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (231 citations), Complementary and Manual Therapy (21 citations), Cancer Research (131 citations), Pathology and Forensic Medicine (149 citations) and Developmental Neuroscience (29 citations). Chenying Fu has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Quan Wei, Chengqi He, Qing Zhang, Shiqi Wang, Lu Wang, Hongxin Cheng, Yang Wang, Lin Xu, Gaiqin Pei and Yangfu Jiang. Their work appears in journals such as BMC Cardiovascular Disorders, Clinical Rehabilitation, Journal of Medical Internet Research, Frontiers in Cell and Developmental Biology and Biomedicine & Pharmacotherapy.

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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