Qin Fu

3.1k citations
96 papers · 2.4k · h-index 26

Impact in

Papers in

Qin Fu

91 papers receiving 2.3k citations

Peers

Qin Fu
Comparison fields: 5 of 130
  • Cardiology and Cardiovascular Medicine 456
  • Transplantation 44
  • Geriatrics and Gerontology 43
  • Molecular Biology 886
  • Nephrology 84
Replace Anil Bhanudas Gaikwad with:
Anil Bhanudas Gaikwad India
Nalini Santanam United States
Lee Ann MacMillan-Crow United States
Ziqing Hei China
Mark J. Crabtree United Kingdom
Shimpei Fujimoto Japan
Stefano Menini Italy
Raffaella Mastrocola Italy
Yaw L. Siow Canada
Hideaki Kaneto Japan
Qin Fu relative to Anil Bhanudas Gaikwad India Anil Bhanudas Gaikwad's profile →
Citations per field
00.5×1.5×1.8×
Anil Bhanudas Gaikwad · 1×
Citations per year

Countries citing papers authored by Qin Fu

Since Specialization
Citations

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

Fields of papers citing papers by Qin Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 96 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009221
2 2006137
3 2009134
4 2012119
5 2011107
6 201699
7 200890
8 201384
9 201473
10 201270
11 200569
12 201667
13 200464
14 201263
15 201048
16 201647
17 201746
18 201741
19 201040
20 201432

About Qin Fu

Qin Fu is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine, Physiology and Pharmacology, having authored 96 papers that have together received 2.4k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (11 papers), Phosphodiesterase function and regulation (10 papers), Cardiac electrophysiology and arrhythmias (5 papers), Hemophilia Treatment and Research (5 papers), Cardiovascular Function and Risk Factors (4 papers), Blood Coagulation and Thrombosis Mechanisms (4 papers), Cardiovascular Issues in Pregnancy (4 papers) and Pharmacological Effects and Assays (4 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (456 citations), Transplantation (44 citations), Geriatrics and Gerontology (43 citations), Molecular Biology (886 citations) and Nephrology (84 citations). Qin Fu has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Jizhou Xiang, Yang K. Xiang, Benrong Hu, Qian Shi, Bing Xu, Jia-Qing Qian, Yang Xiang, Xiongwen Chen, Jennifer E. Van Eyk and Rong Ma. Their work appears in journals such as Haemophilia, International Journal of Gynecology & Obstetrics, Scientific Reports, Circulation Research and Acta Pharmacologica Sinica.

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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