Dan Xing

4.4k citations
159 papers · 3.3k · h-index 33

Impact in

Papers in

Dan Xing

149 papers receiving 3.2k citations

Peers

Dan Xing
Comparison fields: 5 of 140
  • Rheumatology 801
  • Statistics, Probability and Uncertainty 209
  • Surgery 818
  • Biochemistry 110
  • Genetics 128
Replace Xisheng Weng with:
Xisheng Weng China
Giulio Maccauro Italy
Eleftherios E. Tsiridis Greece
Faleh Tamimi Canada
William James Hozack United States
Emerito Carlos Rodriguez-Merchan Spain
Ian Douglas Learmonth United Kingdom
Markus Tingart Germany
Neil Rushton United Kingdom
Yingze Zhang China
Dan Xing relative to Xisheng Weng China Xisheng Weng's profile →
Citations per field
00.5×2×4×6×8.7×
Xisheng Weng · 1×
Citations per year

Countries citing papers authored by Dan Xing

Since Specialization
Citations

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

Fields of papers citing papers by Dan Xing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 159 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012132
2 2020119
3 2013115
4 2014114
5 2012108
6 201994
7 201693
8 202286
9 202079
10 201877
11 202076
12 201975
13 202062
14 201361
15 202360
16 201656
17 201956
18 202055
19 202153
20 201350

About Dan Xing

Dan Xing is a scholar working on Rheumatology, Statistics, Probability and Uncertainty, Surgery, Ceramics and Composites and Genetics, having authored 159 papers that have together received 3.3k indexed citations. Recurring topics across this work include Osteoarthritis Treatment and Mechanisms (45 papers), scientometrics and bibliometrics research (13 papers), Fiber-reinforced polymer composites (13 papers), Total Knee Arthroplasty Outcomes (10 papers), Musculoskeletal pain and rehabilitation (9 papers), Bone Tissue Engineering Materials (9 papers), Mesenchymal stem cell research (7 papers) and Clinical practice guidelines implementation (6 papers). The work is most often cited by research in Rheumatology (801 citations), Statistics, Probability and Uncertainty (209 citations), Surgery (818 citations), Biochemistry (110 citations) and Genetics (128 citations). Dan Xing has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Jianhao Lin, Peng‐Cheng Ma, Shengjie Dong, Jianxiong Ma, Bin Wang, Xinlong Ma, Jiao Jiao Li, Bin Hao, Weiguo Xu and Qiang Liu. Their work appears in journals such as BMC Musculoskeletal Disorders, Osteoarthritis and Cartilage, Construction and Building Materials, Bioactive Materials and Journal of Non-Crystalline Solids.

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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