Anthony S.L. Chan

791 total citations
25 papers, 664 citations indexed

About

Anthony S.L. Chan is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Oncology. According to data from OpenAlex, Anthony S.L. Chan has authored 25 papers receiving a total of 664 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 9 papers in Cellular and Molecular Neuroscience and 5 papers in Oncology. Recurrent topics in Anthony S.L. Chan's work include Receptor Mechanisms and Signaling (14 papers), Protein Kinase Regulation and GTPase Signaling (9 papers) and Neuropeptides and Animal Physiology (7 papers). Anthony S.L. Chan is often cited by papers focused on Receptor Mechanisms and Signaling (14 papers), Protein Kinase Regulation and GTPase Signaling (9 papers) and Neuropeptides and Animal Physiology (7 papers). Anthony S.L. Chan collaborates with scholars based in Hong Kong, China and United States. Anthony S.L. Chan's co-authors include Yung Hou Wong, Angel Y.F. Kam, Rico K.H. Lo, Y.K. Tam, Eric J. Stanbridge, T. Voyno-Yasenetskaya, Frank P.L. Lai, Yun K. Tam, Linda W.C. Ng and Winnie Chan and has published in prestigious journals such as Journal of Molecular Biology, Journal of Neurochemistry and Journal of Pharmacology and Experimental Therapeutics.

In The Last Decade

Anthony S.L. Chan

25 papers receiving 652 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anthony S.L. Chan Hong Kong 15 392 202 135 77 63 25 664
Bruce R. Bianchi United States 17 356 0.9× 299 1.5× 171 1.3× 34 0.4× 346 5.5× 32 1.1k
Sue Yu United States 11 370 0.9× 254 1.3× 84 0.6× 18 0.2× 147 2.3× 22 943
Guillermo García‐Santos Spain 16 393 1.0× 106 0.5× 520 3.9× 50 0.6× 138 2.2× 21 945
Pil‐Jae Kong South Korea 9 169 0.4× 79 0.4× 90 0.7× 19 0.2× 79 1.3× 11 482
Jiying Jiang China 13 333 0.8× 96 0.5× 223 1.7× 28 0.4× 121 1.9× 27 773
Myung Bok Wie South Korea 13 195 0.5× 88 0.4× 36 0.3× 17 0.2× 94 1.5× 19 565
Nathalie Linck France 15 304 0.8× 131 0.6× 30 0.2× 21 0.3× 144 2.3× 21 757
Sara L. Morales‐Lázaro Mexico 21 563 1.4× 228 1.1× 40 0.3× 23 0.3× 331 5.3× 35 1.1k
Shuohui Gao China 18 394 1.0× 38 0.2× 49 0.4× 89 1.2× 105 1.7× 33 890

Countries citing papers authored by Anthony S.L. Chan

Since Specialization
Citations

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

Fields of papers citing papers by Anthony S.L. Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anthony S.L. Chan. 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 Anthony S.L. Chan. The network helps show where Anthony S.L. Chan may publish in the future.

Co-authorship network of co-authors of Anthony S.L. Chan

This figure shows the co-authorship network connecting the top 25 collaborators of Anthony S.L. Chan. A scholar is included among the top collaborators of Anthony S.L. Chan 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 Anthony S.L. Chan. Anthony S.L. Chan 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.
Chan, Anthony S.L., et al.. (2016). Differential Regulation of CXCL8 Production by Different G Protein Subunits with Synergistic Stimulation by G i - and G q -Regulated Pathways. Journal of Molecular Biology. 428(19). 3869–3884. 4 indexed citations
2.
Chan, Anthony S.L., et al.. (2015). An intact helical domain is required for Gα14 to stimulate phospholipase Cβ. BMC Structural Biology. 15(1). 18–18. 2 indexed citations
3.
Zuo, Hao, Anthony S.L. Chan, Hermann Ammer, & Yung Hou Wong. (2013). Activation of Gαq subunits up-regulates the expression of the tumor suppressor Fhit. Cellular Signalling. 25(12). 2440–2452. 3 indexed citations
4.
Zuo, Hao, et al.. (2013). Activation state-dependent interaction between Gαq subunits and the Fhit tumor suppressor. Cell Communication and Signaling. 11(1). 59–59. 7 indexed citations
5.
Wang, Yingchun, et al.. (2010). RGS19 enhances cell proliferation through its C-terminal PDZ motif. Cellular Signalling. 22(11). 1700–1707. 15 indexed citations
6.
Chan, Anthony S.L., et al.. (2010). Activation of STAT3 by specific Gα subunits and multiple Gβγ dimers. The International Journal of Biochemistry & Cell Biology. 42(6). 1052–1059. 25 indexed citations
7.
Chan, Anthony S.L., et al.. (2009). Gβ3 forms distinct dimers with specific Gγ subunits and preferentially activates the β3 isoform of phospholipase C. Cellular Signalling. 21(5). 737–744. 23 indexed citations
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Chan, Anthony S.L., et al.. (2006). Protocatechuic acid induces cell death in HepG2 hepatocellular carcinoma cells through a c-Jun N-terminal kinase-dependent mechanism. Cell Biology and Toxicology. 22(4). 293–302. 106 indexed citations
10.
Chan, Anthony S.L., et al.. (2006). CKBM stimulates MAPKs but inhibits LPS-induced IFN-γ in lymphocytes. Phytotherapy Research. 20(9). 725–731. 9 indexed citations
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Chan, Anthony S.L., et al.. (2005). Integration of G protein signals by extracellular signal‐regulated protein kinases in SK‐N‐MC neuroepithelioma cells. Journal of Neurochemistry. 94(5). 1457–1470. 27 indexed citations
14.
Kam, Angel Y.F., Anthony S.L. Chan, & Yung Hou Wong. (2004). κ-Opioid Receptor Signals through Src and Focal Adhesion Kinase to Stimulate c-Jun N-Terminal Kinases in Transfected COS-7 Cells and Human Monocytic THP-1 Cells. Journal of Pharmacology and Experimental Therapeutics. 310(1). 301–310. 36 indexed citations
15.
Kam, Angel Y.F., Anthony S.L. Chan, & Yung Hou Wong. (2004). Phosphatidylinositol‐3 kinase is distinctively required for µ‐, but not κ‐opioid receptor‐induced activation of c‐Jun N‐terminal kinase. Journal of Neurochemistry. 89(2). 391–402. 42 indexed citations
16.
Chan, Anthony S.L. & Yung Hou Wong. (2004). Gβγ signaling and Ca2+ mobilization co-operate synergistically in a Sos and Rac-dependent manner in the activation of JNK by Gq-coupled receptors. Cellular Signalling. 16(7). 823–836. 13 indexed citations
17.
Chan, Anthony S.L. & Yung Hou Wong. (2004). Epidermal growth factor differentially augments Gi‐mediated stimulation of c‐Jun N‐terminal kinase activity. British Journal of Pharmacology. 142(4). 635–646. 12 indexed citations
18.
Kam, Angel Y.F., Anthony S.L. Chan, & Yung Hou Wong. (2003). Rac and Cdc42‐dependent regulation of c‐Jun N‐terminal kinases by the δ‐opioid receptor. Journal of Neurochemistry. 84(3). 503–513. 43 indexed citations
19.
Chan, Anthony S.L., Frank P.L. Lai, Rico K.H. Lo, et al.. (2002). Melatonin mt1 and MT2 receptors stimulate c-Jun N-terminal kinase via pertussis toxin-sensitive and -insensitive G proteins. Cellular Signalling. 14(3). 249–257. 124 indexed citations
20.
Chan, Anthony S.L. & Yung Hou Wong. (2000). Regulation of c-Jun N-Terminal Kinase by the ORL1Receptor through Multiple G Proteins. Journal of Pharmacology and Experimental Therapeutics. 295(3). 1094–1100. 37 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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