Yaping Feng

1.7k total citations
88 papers, 1.2k citations indexed

About

Yaping Feng is a scholar working on Molecular Biology, Surgery and Internal Medicine. According to data from OpenAlex, Yaping Feng has authored 88 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 12 papers in Surgery and 10 papers in Internal Medicine. Recurrent topics in Yaping Feng's work include Venous Thromboembolism Diagnosis and Management (10 papers), Pain Mechanisms and Treatments (7 papers) and Osteoarthritis Treatment and Mechanisms (7 papers). Yaping Feng is often cited by papers focused on Venous Thromboembolism Diagnosis and Management (10 papers), Pain Mechanisms and Treatments (7 papers) and Osteoarthritis Treatment and Mechanisms (7 papers). Yaping Feng collaborates with scholars based in China, United States and Poland. Yaping Feng's co-authors include Andrzej Kloczkowski, Robert L. Jernigan, Xing Long, Dibyendu Kumar, Joachim Messing, Ke Jin, Taner Z. Sen, Ganwu Li, John V. Garcia and Lisa K. Nolan and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Advanced Materials and PLoS ONE.

In The Last Decade

Yaping Feng

84 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yaping Feng China 19 519 176 137 122 121 88 1.2k
Zhihua Liu China 18 514 1.0× 67 0.4× 80 0.6× 163 1.3× 81 0.7× 39 1.1k
Mark A. Hancock Canada 25 1.2k 2.2× 77 0.4× 46 0.3× 234 1.9× 184 1.5× 53 2.2k
Keiko Sakamoto Japan 18 594 1.1× 32 0.2× 75 0.5× 197 1.6× 180 1.5× 62 1.2k
Min Jiao China 20 718 1.4× 113 0.6× 145 1.1× 151 1.2× 130 1.1× 82 1.5k
Christopher T. Turner Australia 20 487 0.9× 81 0.5× 61 0.4× 200 1.6× 88 0.7× 46 1.2k
Xiaoxiao Zhou China 18 630 1.2× 57 0.3× 94 0.7× 136 1.1× 68 0.6× 77 1.3k
Fernando S. Santiago Australia 23 1.2k 2.4× 58 0.3× 57 0.4× 230 1.9× 203 1.7× 33 1.9k
Piotr Bielecki Germany 20 929 1.8× 42 0.2× 67 0.5× 387 3.2× 159 1.3× 30 1.7k
Yanqiu Li China 19 359 0.7× 70 0.4× 85 0.6× 80 0.7× 53 0.4× 128 1.3k

Countries citing papers authored by Yaping Feng

Since Specialization
Citations

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

Fields of papers citing papers by Yaping Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yaping Feng

This figure shows the co-authorship network connecting the top 25 collaborators of Yaping Feng. A scholar is included among the top collaborators of Yaping Feng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yaping Feng. Yaping Feng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Fang, Wei, Yaping Feng, Xin Liu, et al.. (2025). Bafilomycin A1 mitigates subchondral bone degeneration and pain in TMJOA rats. International Immunopharmacology. 147. 113947–113947. 5 indexed citations
3.
Feng, Yaping, et al.. (2024). Bimetallic MOF-derived manganese-cobalt composite oxide as high-performance zinc-ion batteries cathode. Journal of Solid State Electrochemistry. 29(1). 239–248. 3 indexed citations
4.
Liu, Wen, et al.. (2024). Changes of Trigeminal Ganglion Neurons Innervating the Temporomandibular Joint in Chronic Pain Rat Model. International Journal of Dentistry. 2024(1). 7015382–7015382. 2 indexed citations
5.
Jiang, Hongxin, et al.. (2023). Progress in understanding resistant-starch formation in hydroxypropyl starch: A minireview. Food Hydrocolloids. 149. 109628–109628. 9 indexed citations
6.
Li, Huimin, et al.. (2023). ALPK1 Expressed in IB4-Positive Neurons of Mice Trigeminal Ganglions Promotes MIA-Induced TMJ pain. Molecular Neurobiology. 60(11). 6264–6274. 4 indexed citations
7.
Zhang, Youfeng, Shasha He, Yichen Zhang, et al.. (2022). Preparation of MoS2 and MoO3 Modified TiO2 Composites with Enhanced Visible-light Photocatalytic Activity for Dye Degradation. International Journal of Electrochemical Science. 17(2). 220210–220210. 8 indexed citations
8.
Feng, Yaping, Shiyu Hu, Li Liu, Ke Jin, & Xing Long. (2020). HMGB1 contributes to osteoarthritis of temporomandibular joint by inducing synovial angiogenesis. Journal of Oral Rehabilitation. 48(5). 551–559. 12 indexed citations
9.
Liu, Li, Yaping Feng, Shiyu Hu, et al.. (2020). PDCD4 suppresses autophagy and promotes apoptosis via Akt in chondrocytes of temporomandibular joint osteoarthritis. Oral Diseases. 27(3). 547–558. 3 indexed citations
10.
Liu, Xin, Yaping Feng, Wen Liu, et al.. (2020). Toll‐like receptor 2 mediates the degeneration of cartilage in experimental inflammatory TMJOA. Oral Diseases. 28(2). 415–427. 1 indexed citations
11.
Li, Huimin, Yaping Feng, Ke Jin, et al.. (2020). Cross-talk between synovial fibroblasts and chondrocytes in condylar hyperplasia: an in vitro pilot study. Oral Surgery Oral Medicine Oral Pathology and Oral Radiology. 131(5). 558–564. 3 indexed citations
12.
Liu, Xin, Hengxing Cai, Yaping Feng, et al.. (2020). TLR4 contributes to the damage of cartilage and subchondral bone in discectomy‐induced TMJOA mice. Journal of Cellular and Molecular Medicine. 24(19). 11489–11499. 25 indexed citations
13.
Piccoli, Benedetto, Yaping Feng, Laura Scheinfeldt, et al.. (2019). Habitat-Specific Clock Variation and Its Consequence on Reproductive Fitness. Journal of Biological Rhythms. 35(2). 134–144. 7 indexed citations
14.
Pareek, Chandra S., J. M. Jaśkowski, Mariusz T. Skowroński, et al.. (2019). Comparative Analysis of the Liver Transcriptome among Cattle Breeds Using RNA-seq. Veterinary Sciences. 6(2). 36–36. 11 indexed citations
15.
Li, Huimin, Chang Lei, Li Liu, et al.. (2019). Nanotherapy in Joints: Increasing Endogenous Hyaluronan Production by Delivering Hyaluronan Synthase 2. Advanced Materials. 31(46). e1904535–e1904535. 72 indexed citations
16.
Li, Yin, Wenqin Wang, Yaping Feng, et al.. (2018). Transcriptome and metabolome reveal distinct carbon allocation patterns during internode sugar accumulation in different sorghum genotypes. Plant Biotechnology Journal. 17(2). 472–487. 60 indexed citations
17.
Sun, Mingli, Yaping Feng, Jun Huang, & Yong Wang. (2017). [Clinical features of hospitalized patients with deep venous thrombosis].. PubMed. 56(12). 914–918. 1 indexed citations
18.
Zhang, Zhijian, et al.. (2015). Strategies for the decoupling effect of carbon emission and low carbon in the logistics industry of jiangxi province: From the perspective of environmental protection. Nature Environment and Pollution Technology. 14(4). 995. 1 indexed citations
19.
Zhang, Wei, et al.. (2015). Genome-wide histone acetylation correlates with active transcription in maize. Genomics. 106(4). 214–220. 23 indexed citations
20.
Feng, Yaping, Robert L. Jernigan, & Andrzej Kloczkowski. (2008). Orientational distributions of contact clusters in proteins closely resemble those of an icosahedron. Proteins Structure Function and Bioinformatics. 73(3). 730–741. 5 indexed citations

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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