Su Fu

1.0k citations
57 papers · 785 · h-index 15

Impact in

  • Genetics top 10%
    • Mesenchymal stem cell research
  • Parasitology top 10%
    • Vector-borne infectious diseases

Papers in

    • Tissue Engineering and Regenerative Medicine 13
    • Breast Implant and Reconstruction 4
    • Mesenchymal stem cell research 12

Su Fu

56 papers receiving 780 citations

Peers

Su Fu
Comparison fields: 5 of 94
  • Genetics 144
  • Parasitology 54
  • Cellular and Molecular Neuroscience 117
  • Orthopedics and Sports Medicine 44
  • Biomaterials 63
Replace Soung Hoo Jeon with:
Soung Hoo Jeon South Korea
Xueling Chen China
Ingo Riederer Brazil
Muhammad Daud Malaysia
Li Deng China
Dong‐In Jung South Korea
Javier Esparza Spain
David O. Zamora United States
Toshiro Yoshimura Japan
Francis M. Chen Hong Kong
Su Fu relative to Soung Hoo Jeon South Korea Soung Hoo Jeon's profile →
Citations per field
00.5×
Soung Hoo Jeon · 1×
Citations per year

Countries citing papers authored by Su Fu

Since Specialization
Citations

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

Fields of papers citing papers by Su Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020111
2 201861
3 201361
4 201451
5 201551
6 201441
7 201334
8 201733
9 201430
10 201730
11 201324
12 201520
13 201316
14 201815
15 201914
16 201913
17 201613
18 202213
19 201612
20 202110

About Su Fu

Su Fu is a scholar working on Surgery, Genetics, Molecular Biology, Cellular and Molecular Neuroscience and Biomaterials, having authored 57 papers that have together received 785 indexed citations. Recurring topics across this work include Tissue Engineering and Regenerative Medicine (13 papers), Mesenchymal stem cell research (12 papers), Electrospun Nanofibers in Biomedical Applications (8 papers), Neuropeptides and Animal Physiology (7 papers), Axon Guidance and Neuronal Signaling (5 papers), Spine and Intervertebral Disc Pathology (4 papers), Breast Implant and Reconstruction (4 papers) and Wnt/β-catenin signaling in development and cancer (3 papers). The work is most often cited by research in Genetics (144 citations), Parasitology (54 citations), Cellular and Molecular Neuroscience (117 citations), Orthopedics and Sports Medicine (44 citations) and Biomaterials (63 citations). Su Fu has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Jie Luan, Martin M. Knight, Hannah K. Heywood, Stephen D. Thorpe, Clare L. Thompson, Qian Wang, Minqiang Xin, Dan Jin, Jianqun Wu and Dan Jin. Their work appears in journals such as Aesthetic Plastic Surgery, Aesthetic Surgery Journal, Plastic & Reconstructive Surgery, Annals of Plastic Surgery and Scientific Reports.

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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