Dehua Yang

13.8k total citations · 3 hit papers
250 papers, 6.5k citations indexed

About

Dehua Yang is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Dehua Yang has authored 250 papers receiving a total of 6.5k indexed citations (citations by other indexed papers that have themselves been cited), including 115 papers in Molecular Biology, 50 papers in Cellular and Molecular Neuroscience and 39 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Dehua Yang's work include Receptor Mechanisms and Signaling (51 papers), Neuropeptides and Animal Physiology (37 papers) and Diabetes Treatment and Management (31 papers). Dehua Yang is often cited by papers focused on Receptor Mechanisms and Signaling (51 papers), Neuropeptides and Animal Physiology (37 papers) and Diabetes Treatment and Management (31 papers). Dehua Yang collaborates with scholars based in China, United States and Japan. Dehua Yang's co-authors include Ming‐Wei Wang, Weidong Le, Sheng Chen, Antao Dai, Qingtong Zhou, Xiaoqing Cai, Raymond C. Stevens, Bing Huang, Jie Jia and Jie Xiong and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Dehua Yang

234 papers receiving 6.5k citations

Hit Papers

Common activation mechani... 2016 2026 2019 2022 2019 2021 2016 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Dehua Yang 3.7k 1.7k 843 613 548 250 6.5k
Lei Zhang 4.6k 1.2× 2.2k 1.3× 328 0.4× 686 1.1× 878 1.6× 419 9.5k
Jae‐Yong Park 3.1k 0.8× 908 0.5× 732 0.9× 1.1k 1.7× 474 0.9× 275 6.6k
Dobromir Dobrev 7.5k 2.0× 1.3k 0.8× 349 0.4× 768 1.3× 631 1.2× 309 17.4k
Glenn I. Fishman 7.7k 2.0× 1.0k 0.6× 389 0.5× 835 1.4× 526 1.0× 136 11.1k
Robert M. Graham 5.8k 1.6× 2.0k 1.2× 684 0.8× 1.4k 2.3× 1.6k 3.0× 268 12.7k
Tao Xu 5.0k 1.3× 2.0k 1.2× 223 0.3× 880 1.4× 904 1.6× 282 9.4k
Fulvio Magni 2.8k 0.8× 1.2k 0.7× 425 0.5× 384 0.6× 903 1.6× 284 6.8k
Hemal H. Patel 4.2k 1.1× 725 0.4× 232 0.3× 686 1.1× 1.1k 2.0× 213 8.1k
Xander H.T. Wehrens 10.2k 2.7× 1.9k 1.1× 281 0.3× 680 1.1× 786 1.4× 266 15.3k
Biaoyang Lin 5.4k 1.4× 1.3k 0.8× 280 0.3× 244 0.4× 240 0.4× 121 8.0k

Countries citing papers authored by Dehua Yang

Since Specialization
Citations

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

Fields of papers citing papers by Dehua Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dehua Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Dehua Yang. A scholar is included among the top collaborators of Dehua Yang 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 Dehua Yang. Dehua Yang 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.
Wu, Canrong, Yong Zhang, Antao Dai, et al.. (2025). Molecular mechanisms of urate transport by the native human URAT1 and its inhibition by anti-gout drugs. Cell Discovery. 11(1). 33–33. 2 indexed citations
3.
Cao, Yinglong, Chao Zhang, Qingning Yuan, et al.. (2025). Mechanisms of chemokine recognition and receptor activation of chemokine receptor CCR7. Cell Reports. 44(11). 116582–116582.
4.
Chen, Yan, Qingtong Zhou, Shiyu Yan, et al.. (2025). Molecular mechanism underlying non-discriminatory recognition of relaxin-3 by RXFP3 and RXFP4. Communications Biology. 8(1). 794–794.
5.
Li, Jie, et al.. (2024). Molecular basis of enhanced GLP-1 signaling mediated by GLP-1(9–36) in conjunction with LSN3318839. Acta Pharmaceutica Sinica B. 14(11). 5069–5073. 1 indexed citations
6.
Li, Linhai, Dehua Yang, Xiao Li, et al.. (2024). High‐Efficiency Separation of Near‐Zigzag Single‐Chirality Carbon Nanotubes by Gel Chromatography. physica status solidi (b). 262(3). 1 indexed citations
7.
Li, Cuixia, Yiran Wu, Wenli Wang, et al.. (2023). Structure-Based Ligand Discovery Targeting the Transmembrane Domain of Frizzled Receptor FZD7. Journal of Medicinal Chemistry. 66(17). 11855–11868. 8 indexed citations
8.
He, Xinheng, Antao Dai, Dehua Yang, et al.. (2023). Identification of a carbohydrate recognition motif of purinergic receptors. eLife. 12. 4 indexed citations
9.
Chen, Yan, Qingtong Zhou, Jiang Wang, et al.. (2023). Ligand recognition mechanism of the human relaxin family peptide receptor 4 (RXFP4). Nature Communications. 14(1). 492–492. 7 indexed citations
10.
Cong, Zhaotong, Qingtong Zhou, Yang Li, et al.. (2022). Structural basis of peptidomimetic agonism revealed by small-molecule GLP-1R agonists Boc5 and WB4-24. Proceedings of the National Academy of Sciences. 119(20). e2200155119–e2200155119. 25 indexed citations
11.
Hart, Jonathan R., Xiao Liu, Lynn Ueno, et al.. (2022). Nanobodies and chemical cross-links advance the structural and functional analysis of PI3Kα. Proceedings of the National Academy of Sciences. 119(38). e2210769119–e2210769119. 11 indexed citations
12.
Cheng, Xi, Lihua Zhao, Yuzhe Wang, et al.. (2021). Molecular insights into differentiated ligand recognition of the human parathyroid hormone receptor 2. Proceedings of the National Academy of Sciences. 118(32). 25 indexed citations
13.
Lin, Guangyao, Yang Feng, Xiaoqing Cai, et al.. (2021). High-Throughput Screening Campaign Identified a Potential Small Molecule RXFP3/4 Agonist. Molecules. 26(24). 7511–7511. 5 indexed citations
14.
Feng, Mei, Yan Zhou, Shenglin Mei, et al.. (2021). BCL9 regulates CD226 and CD96 checkpoints in CD8+ T cells to improve PD-1 response in cancer. Signal Transduction and Targeted Therapy. 6(1). 313–313. 28 indexed citations
15.
Liu, Xiao, Jonathan R. Hart, Xinyu Zou, et al.. (2021). Cryo-EM structures of PI3Kα reveal conformational changes during inhibition and activation. Proceedings of the National Academy of Sciences. 118(45). 25 indexed citations
16.
Lu, Yan, Hongyue Liu, Dehua Yang, et al.. (2021). Affinity Mass Spectrometry-Based Fragment Screening Identified a New Negative Allosteric Modulator of the Adenosine A2A Receptor Targeting the Sodium Ion Pocket. ACS Chemical Biology. 16(6). 991–1002. 18 indexed citations
17.
Han, Shuo, Xinmei Li, Peishen Zhao, et al.. (2020). Structural basis of G s and G i recognition by the human glucagon receptor. Science. 367(6484). 1346–1352. 110 indexed citations
18.
Zhang, Bingjie, Simeng Zhao, Dehua Yang, et al.. (2020). A Novel G Protein-Biased and Subtype-Selective Agonist for a G Protein-Coupled Receptor Discovered from Screening Herbal Extracts. ACS Central Science. 6(2). 213–225. 36 indexed citations
19.
Zhou, Yan, Daohai Du, Jia Wang, et al.. (2020). Identification of catalytic and non‐catalytic activity inhibitors against PRC2‐EZH2 complex through multiple high‐throughput screening campaigns. Chemical Biology & Drug Design. 96(4). 1024–1051. 7 indexed citations
20.
Zhou, Qingtong, Dehua Yang, Meng Wu, et al.. (2019). Common activation mechanism of class A GPCRs. eLife. 8. 396 indexed citations breakdown →

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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