Ming‐Shiu Hung

1.5k total citations
36 papers, 1.2k citations indexed

About

Ming‐Shiu Hung is a scholar working on Molecular Biology, Pharmacology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Ming‐Shiu Hung has authored 36 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 16 papers in Pharmacology and 12 papers in Cellular and Molecular Neuroscience. Recurrent topics in Ming‐Shiu Hung's work include Cannabis and Cannabinoid Research (15 papers), Neurotransmitter Receptor Influence on Behavior (9 papers) and Pharmacological Receptor Mechanisms and Effects (8 papers). Ming‐Shiu Hung is often cited by papers focused on Cannabis and Cannabinoid Research (15 papers), Neurotransmitter Receptor Influence on Behavior (9 papers) and Pharmacological Receptor Mechanisms and Effects (8 papers). Ming‐Shiu Hung collaborates with scholars based in Taiwan, United States and Germany. Ming‐Shiu Hung's co-authors include C.‐K. James Shen, Jen‐Shin Song, Kak‐Shan Shia, Wen‐Chi Hsiao, Yu‐Sheng Chao, Bau‐Lin Huang, Karthikeyan Narayanan, Su‐Ying Wu, Mine-Hsine Wu and Hshi-chi Koo and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Ming‐Shiu Hung

36 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
Ming‐Shiu Hung Taiwan 21 508 217 182 177 157 36 1.2k
María Dolores Martin‐de‐Saavedra Spain 20 518 1.0× 178 0.8× 174 1.0× 266 1.5× 62 0.4× 36 1.2k
Agnès Petit-Paitel France 20 797 1.6× 306 1.4× 123 0.7× 462 2.6× 52 0.3× 38 2.0k
Kathy L. Kohlhaas United States 19 674 1.3× 179 0.8× 42 0.2× 290 1.6× 222 1.4× 33 1.2k
Hyung Wook Nam United States 21 1.2k 2.4× 122 0.6× 41 0.2× 328 1.9× 285 1.8× 47 1.9k
James Stoll United States 20 669 1.3× 90 0.4× 41 0.2× 240 1.4× 125 0.8× 32 1.4k
Dorota Łażewska Poland 24 746 1.5× 209 1.0× 30 0.2× 178 1.0× 305 1.9× 86 1.4k
Ge� Xiao United States 12 480 0.9× 162 0.7× 74 0.4× 596 3.4× 179 1.1× 18 1.4k
Paola Tarroni Italy 15 572 1.1× 113 0.5× 62 0.3× 320 1.8× 36 0.2× 22 931
Dominique Demeyer France 14 316 0.6× 119 0.5× 86 0.5× 262 1.5× 56 0.4× 24 906
Joanne R. Mathiasen United States 19 643 1.3× 106 0.5× 28 0.2× 443 2.5× 155 1.0× 51 1.2k

Countries citing papers authored by Ming‐Shiu Hung

Since Specialization
Citations

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

Fields of papers citing papers by Ming‐Shiu Hung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming‐Shiu Hung. 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 Ming‐Shiu Hung. The network helps show where Ming‐Shiu Hung may publish in the future.

Co-authorship network of co-authors of Ming‐Shiu Hung

This figure shows the co-authorship network connecting the top 25 collaborators of Ming‐Shiu Hung. A scholar is included among the top collaborators of Ming‐Shiu Hung 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 Ming‐Shiu Hung. Ming‐Shiu Hung 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.
Huang, Wei‐Cheng, et al.. (2024). Decrypting orphan GPCR drug discovery via multitask learning. Journal of Cheminformatics. 16(1). 10–10. 2 indexed citations
2.
Yang, Cheng‐Wei, Hsing‐Yu Hsu, Yue‐Zhi Lee, et al.. (2023). Natural fucoidans inhibit coronaviruses by targeting viral spike protein and host cell furin. Biochemical Pharmacology. 215. 115688–115688. 12 indexed citations
3.
Hsin, Kun‐Yi, et al.. (2019). A structure-function approach identifies L-PGDS as a mediator responsible for glucocorticoid-induced leptin expression in adipocytes. Biochemical Pharmacology. 166. 203–211. 6 indexed citations
4.
Chang, Chun‐Ping, Jing‐Kai Huang, Ming‐Shiu Hung, et al.. (2018). Fluorine-18 isotope labeling for positron emission tomography imaging. Direct evidence for DBPR211 as a peripherally restricted CB1 inverse agonist. Bioorganic & Medicinal Chemistry. 27(1). 216–223. 7 indexed citations
5.
Hsu, Shu-Ching, Cheng–Yuan Kao, Wenhui Cheng, et al.. (2018). DUSP6 mediates T cell receptor-engaged glycolysis and restrains T FH cell differentiation. Proceedings of the National Academy of Sciences. 115(34). E8027–E8036. 42 indexed citations
6.
Chang, Chia‐Chu, Chia‐Chu Chang, Chen‐Yu Chen, et al.. (2017). Caveolin‐1 Secreted from Adipose Tissues and Adipocytes Functions as an Adipogenesis Enhancer. Obesity. 25(11). 1932–1940. 26 indexed citations
7.
Lee, Yen-Hsien, Lung Yu, Hsin-Jung Lee, et al.. (2016). Orexins contribute to restraint stress-induced cocaine relapse by endocannabinoid-mediated disinhibition of dopaminergic neurons. Nature Communications. 7(1). 12199–12199. 93 indexed citations
8.
Wu, Jian‐Sung, Shu‐Yu Lin, Wen‐Chi Hsiao, et al.. (2015). Identification of Substituted Naphthotriazolediones as Novel Tryptophan 2,3-Dioxygenase (TDO) Inhibitors through Structure-Based Virtual Screening. Journal of Medicinal Chemistry. 58(19). 7807–7819. 48 indexed citations
9.
Hung, Ming‐Shiu, Jen‐Shin Song, Shu‐Yu Lin, et al.. (2014). Discovery and structure–activity relationships of phenyl benzenesulfonylhydrazides as novel indoleamine 2,3-dioxygenase inhibitors. Bioorganic & Medicinal Chemistry Letters. 24(15). 3403–3406. 44 indexed citations
10.
Wu, Yen‐Ku, et al.. (2011). A New Perspective of Cannabinoid 1 Receptor Antagonists: Approaches Toward Peripheral CB1R Blockers without Crossing the Blood-Brain Barrier. Current Topics in Medicinal Chemistry. 11(12). 1421–1429. 20 indexed citations
12.
Shia, Kak‐Shan, Wen‐Chi Hsiao, Teng‐Kuang Yeh, et al.. (2010). Biphasic suppression of appetite by cannabinoid CB1 receptor antagonists with distinct functional activities. Pharmacological Research. 62(4). 337–343. 10 indexed citations
14.
Hung, Ming‐Shiu, Min‐Tsang Hsieh, Chun‐Wei Kuo, et al.. (2008). Bioisosteric replacement of the pyrazole 3-carboxamide moiety of rimonabant. A novel series of oxadiazoles as CB1 cannabinoid receptor antagonists. Organic & Biomolecular Chemistry. 6(18). 3399–3399. 10 indexed citations
15.
Hou, Duen‐Ren, et al.. (2008). 1,2,3-Triazole derivatives as new cannabinoid CB1 receptor antagonists. Bioorganic & Medicinal Chemistry Letters. 19(3). 1022–1025. 44 indexed citations
17.
Hung, Ming‐Shiu, Philip Avner, & Ute C. Rogner. (2006). Identification of the transcription factor ARNTL2 as a candidate gene for the type 1 diabetes locus Idd6. Human Molecular Genetics. 15(18). 2732–2742. 33 indexed citations
18.
Rasheva, Vanya I, et al.. (2003). The Eukaryotic DNMT2 Genes Encode a New Class of Cytosine-5 DNA Methyltransferases. Journal of Biological Chemistry. 278(36). 33613–33616. 59 indexed citations
19.
Hung, Ming‐Shiu, Karthikeyan Narayanan, Bau‐Lin Huang, et al.. (1999). Drosophila proteins related to vertebrate DNA (5-cytosine) methyltransferases. Proceedings of the National Academy of Sciences. 96(21). 11940–11945. 81 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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