Wei Yao

5.7k total citations
97 papers, 4.4k citations indexed

About

Wei Yao is a scholar working on Molecular Biology, Oncology and Orthopedics and Sports Medicine. According to data from OpenAlex, Wei Yao has authored 97 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Molecular Biology, 46 papers in Oncology and 45 papers in Orthopedics and Sports Medicine. Recurrent topics in Wei Yao's work include Bone Metabolism and Diseases (44 papers), Bone health and treatments (39 papers) and Bone health and osteoporosis research (37 papers). Wei Yao is often cited by papers focused on Bone Metabolism and Diseases (44 papers), Bone health and treatments (39 papers) and Bone health and osteoporosis research (37 papers). Wei Yao collaborates with scholars based in United States, China and Australia. Wei Yao's co-authors include Nancy E. Lane, W.S.S. Jee, Robert O. Ritchie, Mohammad Shahnazari, Zhiqiang Cheng, Lynda F. Bonewald, Mary C. Nakamura, M. Balooch, J.H. Kinney and Min Guan and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Medicine.

In The Last Decade

Wei Yao

96 papers receiving 4.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wei Yao United States 35 2.4k 1.7k 1.3k 464 434 97 4.4k
Martina Rauner Germany 48 3.5k 1.5× 1.5k 0.9× 1.9k 1.4× 601 1.3× 646 1.5× 240 7.3k
Masako Ito Japan 40 3.0k 1.3× 2.4k 1.5× 2.0k 1.5× 536 1.2× 922 2.1× 140 6.5k
Roland Baron United States 30 2.5k 1.0× 799 0.5× 1.1k 0.9× 385 0.8× 273 0.6× 59 4.1k
Hong Zhou Australia 45 3.0k 1.2× 860 0.5× 2.7k 2.0× 711 1.5× 510 1.2× 162 6.9k
Karen E. Callon New Zealand 39 1.7k 0.7× 859 0.5× 986 0.7× 642 1.4× 677 1.6× 98 4.0k
Nadia Rucci Italy 42 2.7k 1.1× 494 0.3× 1.5k 1.1× 388 0.8× 396 0.9× 107 4.8k
Jürg A. Gasser Switzerland 31 1.9k 0.8× 1.4k 0.8× 1.5k 1.1× 503 1.1× 467 1.1× 71 3.9k
Michaela Kneissel Switzerland 42 4.5k 1.9× 1.9k 1.2× 2.3k 1.7× 741 1.6× 501 1.2× 86 7.0k
Sotirios Tetradis United States 39 1.5k 0.6× 1.5k 0.9× 1.9k 1.4× 795 1.7× 649 1.5× 152 5.1k
Yoshiaki Azuma Japan 41 4.9k 2.0× 1.6k 1.0× 2.1k 1.6× 651 1.4× 544 1.3× 108 7.8k

Countries citing papers authored by Wei Yao

Since Specialization
Citations

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

Fields of papers citing papers by Wei Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wei Yao

This figure shows the co-authorship network connecting the top 25 collaborators of Wei Yao. A scholar is included among the top collaborators of Wei Yao 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 Wei Yao. Wei Yao 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.
Ding, Song, Wenyi Xu, Xueliang Liu, et al.. (2025). Curcumin-loaded nanoscale coordination polymers for ROS scavenging and anti-inflammatory therapy in atherosclerosis. Materials Today Bio. 34. 102152–102152.
2.
Yao, Wei, et al.. (2023). Syringin inhibits endogenous volume regulated anion channel currents of HEK293 cells in hypotonic circumstances. Pharmacology Research & Perspectives. 11(3). e01105–e01105. 4 indexed citations
3.
Yao, Wei, et al.. (2022). Association between hyperglycemia on admission and preoperative deep venous thrombosis in patients with femoral neck fractures. BMC Musculoskeletal Disorders. 23(1). 899–899. 3 indexed citations
4.
Yang, Ran, Yong Zhan, Yi Li, et al.. (2022). The Cellular and Molecular Landscape of Synchronous Pediatric Sialoblastoma and Hepatoblastoma. Frontiers in Oncology. 12. 893206–893206. 7 indexed citations
5.
Jiang, Min, Ruiwu Liu, Lixian Liu, et al.. (2020). Identification of osteogenic progenitor cell-targeted peptides that augment bone formation. Nature Communications. 11(1). 4278–4278. 24 indexed citations
6.
Alonso‐Goulart, Vivian, Qiongyu Li, Gang-yu Liu, et al.. (2020). High Mannose N-Glycans Promote Migration of Bone-Marrow-Derived Mesenchymal Stromal Cells. International Journal of Molecular Sciences. 21(19). 7194–7194. 6 indexed citations
7.
Sun, Meng, et al.. (2020). Measurements of buccal gingival and alveolar crest thicknesses of premolars using a noninvasive method. Medical Ultrasonography. 22(4). 409–409. 9 indexed citations
8.
Zhang, Hongliang, et al.. (2019). Inhibition of mesenchymal stromal cells’ chemotactic effect to ameliorate paraquat-induced pulmonary fibrosis. Toxicology Letters. 307. 1–10. 11 indexed citations
9.
Xu, Xiaobao, Gaomai Yang, Xiangdong Xue, et al.. (2018). A polymer-free, biomimicry drug self-delivery system fabricatedviaa synergistic combination of bottom-up and top-down approaches. Journal of Materials Chemistry B. 6(47). 7842–7853. 14 indexed citations
10.
Xu, Gege, Dayoung Park, Stefanos Kalomoiris, et al.. (2018). FGF2 Induces Migration of Human Bone Marrow Stromal Cells by Increasing Core Fucosylations on N-Glycans of Integrins. Stem Cell Reports. 11(2). 325–333. 31 indexed citations
11.
Zhong, Zhendong, et al.. (2017). Sex dimorphic regulation of osteoprogenitor progesterone in bone stromal cells. Journal of Molecular Endocrinology. 59(4). 351–363. 7 indexed citations
12.
Ringwood, Lorna A., et al.. (2016). A Novel Hybrid Compound LLP2A-Ale Both Prevented and Rescued the Osteoporotic Phenotype in a Mouse Model of Glucocorticoid-Induced Osteoporosis. Calcified Tissue International. 100(1). 67–79. 12 indexed citations
13.
Yao, Wei, et al.. (2015). Assembly of the Arp5 (Actin-related Protein) Subunit Involved in Distinct INO80 Chromatin Remodeling Activities. Journal of Biological Chemistry. 290(42). 25700–25709. 23 indexed citations
14.
Dai, Weiwei, Haiyan Chen, Hongliang Zhang, et al.. (2015). Prevention of glucocorticoid induced bone changes with beta-ecdysone. Bone. 74. 48–57. 28 indexed citations
15.
Collette, Nicole M., Damian C. Genetos, Aris N. Economides, et al.. (2012). Targeted deletion of Sost distal enhancer increases bone formation and bone mass. Proceedings of the National Academy of Sciences. 109(35). 14092–14097. 109 indexed citations
16.
17.
Sabsovich, Ilya, J. David Clark, Guochun Liao, et al.. (2007). Bone microstructure and its associated genetic variability in 12 inbred mouse strains: μCT study and in silico genome scan. Bone. 42(2). 439–451. 30 indexed citations
18.
Buxton, Eric C., Wei Yao, & Nancy E. Lane. (2004). Changes in Serum Receptor Activator of Nuclear Factor-κB Ligand, Osteoprotegerin, and Interleukin-6 Levels in Patients with Glucocorticoid-Induced Osteoporosis Treated with Human Parathyroid Hormone (1–34). The Journal of Clinical Endocrinology & Metabolism. 89(7). 3332–3336. 64 indexed citations
19.
20.
Yao, Wei, W.S.S. Jee, Hua Zhou, et al.. (1999). Anabolic effect of prostaglandin E2 on cortical bone of aged male rats comes mainly from modeling-dependent bone gain. Bone. 25(6). 697–702. 32 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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