Daping Quan

4.4k citations
116 papers · 3.6k · h-index 36

Impact in

Papers in

Daping Quan

114 papers receiving 3.5k citations

Peers

Daping Quan
Comparison fields: 5 of 117
  • Biomaterials 1.6k
  • Cellular and Molecular Neuroscience 1.1k
  • Developmental Neuroscience 189
  • Process Chemistry and Technology 122
  • Molecular Medicine 168
Replace Yandao Gong with:
Yandao Gong China
Mahrokh Dadsetan United States
Xiufang Zhang China
Doris Klee Germany
Lisa J. White United Kingdom
Julian H. George United Kingdom
Peibiao Zhang China
Liumin He China
Masao Tanihara Japan
Thomas Freier Germany
Daping Quan relative to Yandao Gong China Yandao Gong's profile →
Citations per field
00.5×5.0×
Yandao Gong · 1×
Citations per year

Countries citing papers authored by Daping Quan

Since Specialization
Citations

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

Fields of papers citing papers by Daping Quan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 116 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020148
2 2018135
3 2013133
4 2006129
5 2010122
6 2005113
7 201891
8 201091
9 200989
10 200688
11 201385
12 202183
13 200978
14 202277
15 202276
16 200671
17 202069
18 200767
19 201466
20 200664

About Daping Quan

Daping Quan is a scholar working on Biomaterials, Cellular and Molecular Neuroscience, Surgery, Biomedical Engineering and Organic Chemistry, having authored 116 papers that have together received 3.6k indexed citations. Recurring topics across this work include Electrospun Nanofibers in Biomedical Applications (42 papers), Nerve injury and regeneration (37 papers), Tissue Engineering and Regenerative Medicine (31 papers), biodegradable polymer synthesis and properties (17 papers), Bone Tissue Engineering Materials (14 papers), Spinal Cord Injury Research (9 papers), Neurogenesis and neuroplasticity mechanisms (7 papers) and Advanced Polymer Synthesis and Characterization (6 papers). The work is most often cited by research in Biomaterials (1.6k citations), Cellular and Molecular Neuroscience (1.1k citations), Developmental Neuroscience (189 citations), Process Chemistry and Technology (122 citations) and Molecular Medicine (168 citations). Daping Quan has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Kairong Liao, Ying Bai, Zilong Rao, Qingtang Zhu, Xiaolin Liu, Gang‐Biao Jiang, Liumin He, Shihao Chen, Chenguang Zeng and Yuan‐Shan Zeng. Their work appears in journals such as Polymer, Acta Biomaterialia, Biomedical Materials, Biomaterials and Journal of Controlled Release.

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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