Su‐Ying Wu

4.3k total citations
83 papers, 3.2k citations indexed

About

Su‐Ying Wu is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Oncology. According to data from OpenAlex, Su‐Ying Wu has authored 83 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Molecular Biology, 20 papers in Cellular and Molecular Neuroscience and 15 papers in Oncology. Recurrent topics in Su‐Ying Wu's work include Neuropeptides and Animal Physiology (12 papers), Synthesis and biological activity (8 papers) and Receptor Mechanisms and Signaling (8 papers). Su‐Ying Wu is often cited by papers focused on Neuropeptides and Animal Physiology (12 papers), Synthesis and biological activity (8 papers) and Receptor Mechanisms and Signaling (8 papers). Su‐Ying Wu collaborates with scholars based in Taiwan, United States and China. Su‐Ying Wu's co-authors include Nae J. Dun, Lindsay Sawyer, S.L. Dun, Hsing‐Pang Hsieh, Ulrich Förstermann, Pilar Puyol, María Dolores Pérez, L F Tseng, Harald Schmidt and Yu‐Sheng Chao and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Su‐Ying Wu

79 papers receiving 3.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Su‐Ying Wu Taiwan 33 1.4k 685 592 528 362 83 3.2k
Gabriel M. Simon United States 33 3.4k 2.4× 999 1.5× 903 1.5× 466 0.9× 661 1.8× 73 7.0k
László Prókai United States 36 2.2k 1.5× 469 0.7× 717 1.2× 347 0.7× 360 1.0× 197 4.6k
Katarzyna Kieć‐Kononowicz Poland 35 2.3k 1.6× 1.8k 2.6× 584 1.0× 272 0.5× 246 0.7× 294 4.9k
Pablo V. Escribá Spain 42 3.9k 2.8× 420 0.6× 1.0k 1.7× 663 1.3× 328 0.9× 128 5.9k
Takatsugu Hirokawa Japan 31 2.7k 2.0× 325 0.5× 566 1.0× 311 0.6× 308 0.9× 159 4.6k
Keld Fosgerau Denmark 18 2.1k 1.5× 509 0.7× 398 0.7× 383 0.7× 310 0.9× 33 3.6k
Hongwei Jin China 36 2.2k 1.6× 1.4k 2.1× 231 0.4× 417 0.8× 320 0.9× 222 5.5k
Gerald W. Becker United States 30 1.6k 1.1× 242 0.4× 468 0.8× 658 1.2× 341 0.9× 53 4.0k
María L. López-Rodrı́guez Spain 39 2.2k 1.6× 1.0k 1.5× 2.0k 3.3× 261 0.5× 227 0.6× 191 5.4k

Countries citing papers authored by Su‐Ying Wu

Since Specialization
Citations

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

Fields of papers citing papers by Su‐Ying Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Su‐Ying Wu. 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 Su‐Ying Wu. The network helps show where Su‐Ying Wu may publish in the future.

Co-authorship network of co-authors of Su‐Ying Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Su‐Ying Wu. A scholar is included among the top collaborators of Su‐Ying Wu 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 Su‐Ying Wu. Su‐Ying Wu 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.
Peng, Yi‐Hui, Mu‐Chun Li, Wan-Ching Yen, et al.. (2025). Structure-Based Design of Potent and Selective MerTK Inhibitors by Modulating the Conformation of αC Helix. Journal of Medicinal Chemistry. 68(11). 10877–10896.
2.
Gao, Yuwei, et al.. (2025). Antibacterial reuterin as a multifunctional crosslinker for constructing chitosan-based hydrogels to promote infected wound healing. International Journal of Biological Macromolecules. 316(Pt 1). 144494–144494. 1 indexed citations
3.
Wu, Licheng, et al.. (2025). Photocatalyzed Epimerization of Quaternary Stereocenters. Journal of the American Chemical Society. 147(13). 11080–11088. 4 indexed citations
5.
6.
Wang, Yong, Lingling Huang, Xian Zhang, et al.. (2022). Pedigree-based study to identify GOLGB1 as a risk gene for bipolar disorder. Translational Psychiatry. 12(1). 390–390.
7.
Zheng, Yi, Panpan Ye, Yue Zhou, et al.. (2021). LPS-Induced Inflammation Affects Midazolam Clearance in Juvenile Mice in an Age-Dependent Manner. Journal of Inflammation Research. Volume 14. 3697–3706. 3 indexed citations
8.
Lin, Shu‐Yu, Yi-Yu Ke, Wen‐Hsing Lin, et al.. (2019). Discovery of a Furanopyrimidine-Based Epidermal Growth Factor Receptor Inhibitor (DBPR112) as a Clinical Candidate for the Treatment of Non-Small Cell Lung Cancer. Journal of Medicinal Chemistry. 62(22). 10108–10123. 30 indexed citations
9.
Chang, Chun‐Ping, Jen‐Shin Song, Szu‐Huei Wu, et al.. (2011). Discovery of Novel Stem Cell Mobilizers That Target the CXCR4 Receptor. ChemMedChem. 7(2). 209–212. 18 indexed citations
10.
Hsu, Tsu, Chiung‐Tong Chen, Jai‐Hong Cheng, et al.. (2009). (1,3‐Diphenyl‐1H‐Pyrazol‐4‐yl)‐Methylamine Analogues as Inhibitors of Dipeptidyl Peptidases. Journal of the Chinese Chemical Society. 56(5). 1048–1055. 7 indexed citations
11.
Coumar, Mohane Selvaraj, Chang‐Ying Chu, Biing‐Jiun Uang, et al.. (2009). Identification, SAR Studies, and X‐ray Co‐crystallographic Analysis of a Novel Furanopyrimidine Aurora Kinase A Inhibitor. ChemMedChem. 5(2). 255–267. 28 indexed citations
12.
Lu, I-Lin, Shiow‐Ju Lee, Su‐Ying Wu, et al.. (2005). Glutamic acid analogues as potent dipeptidyl peptidase IV and 8 inhibitors. Bioorganic & Medicinal Chemistry Letters. 15(13). 3271–3275. 30 indexed citations
13.
Dun, Nae J., S.L. Dun, Su‐Ying Wu, Craig A. Williams, & Ernest H. Kwok. (2000). Endomorphins: Localization, release and action on rat dorsal horn neurons. Journal of Biomedical Science. 7(3). 213–220. 20 indexed citations
14.
Dornan, Jacqueline, Antony P. Page, Paul Taylor, et al.. (1999). Biochemical and Structural Characterization of a Divergent Loop Cyclophilin from Caenorhabditis elegans. Journal of Biological Chemistry. 274(49). 34877–34883. 42 indexed citations
15.
Williams, Craig A., Su‐Ying Wu, S.L. Dun, Ernest H. Kwok, & Nae J. Dun. (1999). Release of endomorphin-2 like substances from the rat spinal cord. Neuroscience Letters. 273(1). 25–28. 34 indexed citations
16.
Lin, Hsun‐Hsun, Su‐Ying Wu, Chih‐Chia Lai, & Nae J. Dun. (1997). GABA- and glycine-mediated inhibitory postsynaptic potentials in neonatal rat rostral ventrolateral medulla neurons in vitro. Neuroscience. 82(2). 429–442. 20 indexed citations
17.
Wu, Su‐Ying, S.L. Dun, Ulrich Förstermann, & Nae J. Dun. (1997). Nitric oxide and excitatory postsynaptic currents in immature rat sympathetic preganglionic neurons in vitro. Neuroscience. 79(1). 237–245. 32 indexed citations
18.
Dun, Nae J., S.L. Dun, Su‐Ying Wu, & Ulrich Förstermann. (1993). Nitric oxide synthase immunoreactivity in rat superior cervical ganglia and adrenal glands. Neuroscience Letters. 158(1). 51–54. 77 indexed citations
19.
Dun, Nae J., S.L. Dun, Su‐Ying Wu, et al.. (1993). Nitric oxide synthase immunoreactivity in the rat, mouse, cat and squirrel monkey spinal cord. Neuroscience. 54(4). 845–857. 243 indexed citations
20.
Wu, Su‐Ying, et al.. (1991). Serotonin via presynaptic 5-HT1 receptors attenuates synaptic transmission to immature rat motoneurons in vitro. Brain Research. 554(1-2). 111–121. 58 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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