Ching-Ping Chan

615 total citations
8 papers, 457 citations indexed

About

Ching-Ping Chan is a scholar working on Infectious Diseases, Immunology and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Ching-Ping Chan has authored 8 papers receiving a total of 457 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Infectious Diseases, 4 papers in Immunology and 2 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Ching-Ping Chan's work include SARS-CoV-2 and COVID-19 Research (3 papers), T-cell and Retrovirus Studies (2 papers) and interferon and immune responses (2 papers). Ching-Ping Chan is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (3 papers), T-cell and Retrovirus Studies (2 papers) and interferon and immune responses (2 papers). Ching-Ping Chan collaborates with scholars based in Hong Kong and China. Ching-Ping Chan's co-authors include Dong‐Yan Jin, Kam‐Leung Siu, Kwok‐Yung Yuen, Bo‐Jian Zheng, King‐Tung Chin, Kin‐Hang Kok, Chi‐Ping Chan, Pei‐Hui Wang, Kit‐San Yuen and Sin‐Yee Fung and has published in prestigious journals such as Nucleic Acids Research, Journal of Virology and Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms.

In The Last Decade

Ching-Ping Chan

8 papers receiving 453 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ching-Ping Chan Hong Kong 8 249 139 112 95 92 8 457
Jessie Kulsuptrakul United States 6 199 0.8× 83 0.6× 208 1.9× 63 0.7× 30 0.3× 8 417
Xingyu Li China 12 220 0.9× 93 0.7× 159 1.4× 92 1.0× 20 0.2× 28 549
Ebony A. Monson Australia 10 83 0.3× 165 1.2× 206 1.8× 44 0.5× 48 0.5× 14 475
Jennifer M. Hayashi United States 8 389 1.6× 72 0.5× 260 2.3× 37 0.4× 20 0.2× 12 667
Yunkai Zhu China 8 291 1.2× 73 0.5× 174 1.6× 37 0.4× 28 0.3× 13 452
Binbin Ding China 10 124 0.5× 88 0.6× 181 1.6× 115 1.2× 55 0.6× 17 524
Pratima Rawat United States 10 118 0.5× 159 1.1× 305 2.7× 60 0.6× 31 0.3× 14 610
Mark A. Clementz United States 8 533 2.1× 344 2.5× 293 2.6× 74 0.8× 26 0.3× 10 895
Matthew Whelband United Kingdom 4 139 0.6× 52 0.4× 148 1.3× 48 0.5× 23 0.3× 6 344
Juan Fidel Osuna‐Ramos Mexico 14 334 1.3× 77 0.6× 211 1.9× 269 2.8× 15 0.2× 44 655

Countries citing papers authored by Ching-Ping Chan

Since Specialization
Citations

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

Fields of papers citing papers by Ching-Ping Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching-Ping 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 Ching-Ping Chan. The network helps show where Ching-Ping Chan may publish in the future.

Co-authorship network of co-authors of Ching-Ping Chan

This figure shows the co-authorship network connecting the top 25 collaborators of Ching-Ping Chan. A scholar is included among the top collaborators of Ching-Ping 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 Ching-Ping Chan. Ching-Ping Chan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Fung, Sin‐Yee, Kam‐Leung Siu, Huayue Lin, et al.. (2022). SARS-CoV-2 NSP13 helicase suppresses interferon signaling by perturbing JAK1 phosphorylation of STAT1. Cell & Bioscience. 12(1). 36–36. 38 indexed citations
2.
Gao, Weiwei, et al.. (2018). Suppression of gluconeogenic gene transcription by SIK1-induced ubiquitination and degradation of CRTC1. Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms. 1861(3). 211–223. 9 indexed citations
3.
Wang, Pei‐Hui, Sin‐Yee Fung, Weiwei Gao, et al.. (2018). A novel transcript isoform of STING that sequesters cGAMP and dominantly inhibits innate nucleic acid sensing. Nucleic Acids Research. 46(8). 4054–4071. 61 indexed citations
4.
Chaudhary, Vidyanath, Kit‐San Yuen, Jasper Fuk‐Woo Chan, et al.. (2017). Selective Activation of Type II Interferon Signaling by Zika Virus NS5 Protein. Journal of Virology. 91(14). 87 indexed citations
5.
Yuen, Chun‐Kit, Ching-Ping Chan, Sin‐Yee Fung, et al.. (2016). Suppression of Type I Interferon Production by Human T-Cell Leukemia Virus Type 1 Oncoprotein Tax through Inhibition of IRF3 Phosphorylation. Journal of Virology. 90(8). 3902–3912. 31 indexed citations
6.
Siu, Kam‐Leung, Ching-Ping Chan, Kin‐Hang Kok, Patrick C. Y. Woo, & Dong‐Yan Jin. (2014). Comparative analysis of the activation of unfolded protein response by spike proteins of severe acute respiratory syndrome coronavirus and human coronavirus HKU1. Cell & Bioscience. 4(1). 3–3. 36 indexed citations
8.
Chan, Ching-Ping, Kam‐Leung Siu, King‐Tung Chin, et al.. (2006). Modulation of the Unfolded Protein Response by the Severe Acute Respiratory Syndrome Coronavirus Spike Protein. Journal of Virology. 80(18). 9279–9287. 185 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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