Fei Hua

1.9k citations
58 papers · 1.4k · h-index 20

Impact in

    • Sulfur Compounds in Biology
  • Immunology top 10%
    • Immune Cell Function and Interaction
    • IL-33, ST2, and ILC Pathways

Papers in

    • Ion channel regulation and function 6
    • Immune Cell Function and Interaction 7
    • T-cell and B-cell Immunology 4

Fei Hua

56 papers receiving 1.4k citations

Peers

Fei Hua
Comparison fields: 5 of 108
  • Biochemistry 202
  • Immunology 283
  • Cardiology and Cardiovascular Medicine 304
  • Molecular Biology 679
  • Endocrine and Autonomic Systems 54
Replace M. Koji Owada with:
M. Koji Owada Japan
Gabrielle Paulsson‐Berne Sweden
Neil Dufton United Kingdom
Richard Hummel Germany
Michał Bieńkowski Poland
Leonard S. Golfman Canada
Qun S. Zang United States
Marc Délepine France
Silvia Schauer Austria
Masayuki Namiki Japan
Fei Hua relative to M. Koji Owada Japan M. Koji Owada's profile →
Citations per field
00.5×6.3×
M. Koji Owada · 1×
Citations per year

Countries citing papers authored by Fei Hua

Since Specialization
Citations

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

Fields of papers citing papers by Fei Hua

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015123
2 2014114
3 2002114
4 2004103
5 200598
6 201171
7 201670
8 200266
9 201355
10 200449
11 201344
12 201741
13 201539
14 200638
15 202132
16 202030
17 200429
18 201726
19 201723
20 201021

About Fei Hua

Fei Hua is a scholar working on Molecular Biology, Immunology, Cardiology and Cardiovascular Medicine, Oncology and Radiology, Nuclear Medicine and Imaging, having authored 58 papers that have together received 1.4k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (12 papers), Immune Cell Function and Interaction (7 papers), Hemophilia Treatment and Research (7 papers), Cardiac electrophysiology and arrhythmias (6 papers), Blood Coagulation and Thrombosis Mechanisms (6 papers), Ion channel regulation and function (6 papers), Cardiac Arrhythmias and Treatments (4 papers) and T-cell and B-cell Immunology (4 papers). The work is most often cited by research in Biochemistry (202 citations), Immunology (283 citations), Cardiology and Cardiovascular Medicine (304 citations), Molecular Biology (679 citations) and Endocrine and Autonomic Systems (54 citations). Fei Hua has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Robert F. Gilmour, Jin‐Song Bian, Douglas A. Lauffenburger, Zhiyuan Wu, Li Xie, Jeffrey J. Fox, Zhizhong Xie, Mark L. Riccio, Eberhard Bodenschatz and Michael H. Cardone. Their work appears in journals such as CPT Pharmacometrics & Systems Pharmacology, Blood, mAbs, Antioxidants and Redox Signaling and Journal of Thrombosis and Haemostasis.

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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