Ping Leng

523 citations
19 papers · 401 · h-index 11

Impact in

Papers in

Ping Leng

19 papers receiving 397 citations

Peers

Ping Leng
Comparison fields: 5 of 73
  • Rheumatology 85
  • Orthopedics and Sports Medicine 28
  • Urology 20
  • Physiology 73
  • Genetics 26
Replace Masafumi Motohashi with:
Masafumi Motohashi Japan
Guomin Ren Canada
Srećko Sabalić Croatia
Kai Hang China
Samuele Cheri Italy
Takeshi Minashima United States
Fuhua Yan China
H.-S. Lee Taiwan
Pierre Shephard Germany
Ping Leng relative to Masafumi Motohashi Japan Masafumi Motohashi's profile →
Citations per field
00.5×3.7×
Masafumi Motohashi · 1×
Citations per year

Countries citing papers authored by Ping Leng

Since Specialization
Citations

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

Fields of papers citing papers by Ping Leng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1 202087
2 202160
3 200856
4 200951
5
Uninduced adipose-derived stem cells repair the defect of full-thickness hyaline cartilage.
200925
6 202017
7 201816
8 201216
9 200912
10 200912
11 202210
12 20149
13 20226
14 20135
15 20185
16 20245
17
[Experimental research on human insulin-like growth factor I gene transfect the cultured bone marrow mesenchymal stem cells].
20055
18 20193
19
[Repair full-thickness meniscal defects with injectable tissue engineering technique].
20101

About Ping Leng

Ping Leng is a scholar working on Molecular Biology, Surgery, Physiology, Infectious Diseases and Rheumatology, having authored 19 papers that have together received 401 indexed citations. Recurring topics across this work include Knee injuries and reconstruction techniques (3 papers), Virus-based gene therapy research (2 papers), Osteoarthritis Treatment and Mechanisms (2 papers), Erythrocyte Function and Pathophysiology (2 papers), Total Knee Arthroplasty Outcomes (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), SARS-CoV-2 and COVID-19 Research (1 paper) and Hereditary Neurological Disorders (1 paper). The work is most often cited by research in Rheumatology (85 citations), Orthopedics and Sports Medicine (28 citations), Urology (20 citations), Physiology (73 citations) and Genetics (26 citations). Ping Leng has collaborated with scholars based in China, Thailand and United States. Frequent co-authors include Haining Zhang, Haining Zhang, Yi Sun, Zhenghui Li, Chenkai Li, Jie Zhang, Yingzhen Wang, Dawei Li, Xiaohan Guo and Yilei Yang. Their work appears in journals such as Pharmaceutical Biology, Clinical Orthopaedics and Related Research, BioMed Research International, International Immunopharmacology and Orthopedics.

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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