Sisi Kang

1.5k total citations · 1 hit paper
9 papers, 802 citations indexed

About

Sisi Kang is a scholar working on Infectious Diseases, Molecular Biology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Sisi Kang has authored 9 papers receiving a total of 802 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Infectious Diseases, 2 papers in Molecular Biology and 2 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Sisi Kang's work include SARS-CoV-2 and COVID-19 Research (6 papers), COVID-19 Clinical Research Studies (4 papers) and Viral gastroenteritis research and epidemiology (2 papers). Sisi Kang is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (6 papers), COVID-19 Clinical Research Studies (4 papers) and Viral gastroenteritis research and epidemiology (2 papers). Sisi Kang collaborates with scholars based in China, United States and South Korea. Sisi Kang's co-authors include Shoudeng Chen, Xiaoxue Chen, Zhaoxia Huang, Ziliang Zhou, Zhechong Zhou, Qiuyue Chen, Suhua He, Mei Yang, Zhongsi Hong and Hong Shan and has published in prestigious journals such as Nature Communications, Frontiers in Immunology and British Journal of Anaesthesia.

In The Last Decade

Sisi Kang

9 papers receiving 793 citations

Hit Papers

Crystal structure of SARS-CoV-2 nucleocapsid protein RNA ... 2020 2026 2022 2024 2020 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sisi Kang China 7 528 355 92 91 83 9 802
Zhechong Zhou China 7 527 1.0× 268 0.8× 91 1.0× 91 1.0× 82 1.0× 10 686
Suhua He China 9 548 1.0× 288 0.8× 91 1.0× 91 1.0× 82 1.0× 14 748
Tiffany Tang United States 10 707 1.3× 249 0.7× 80 0.9× 77 0.8× 46 0.6× 12 912
Natacha S. Ogando Netherlands 12 778 1.5× 403 1.1× 91 1.0× 91 1.0× 57 0.7× 22 1.1k
Miya K. Bidon United States 4 587 1.1× 208 0.6× 70 0.8× 70 0.8× 36 0.4× 5 744
Naveen Vankadari Australia 10 651 1.2× 278 0.8× 96 1.0× 119 1.3× 29 0.3× 22 958
Yunru Yang China 11 357 0.7× 277 0.8× 68 0.7× 26 0.3× 67 0.8× 19 624
Ting Shu China 10 534 1.0× 274 0.8× 136 1.5× 54 0.6× 26 0.3× 22 798
Ahmed Mohammed Sudan 7 314 0.6× 183 0.5× 47 0.5× 45 0.5× 50 0.6× 13 458
Matthew Hackbart United States 7 418 0.8× 161 0.5× 124 1.3× 78 0.9× 19 0.2× 9 589

Countries citing papers authored by Sisi Kang

Since Specialization
Citations

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

Fields of papers citing papers by Sisi Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sisi Kang

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

All Works

9 of 9 papers shown
1.
Yang, Mei, Suhua He, Xiaoxue Chen, et al.. (2021). Structural Insight Into the SARS-CoV-2 Nucleocapsid Protein C-Terminal Domain Reveals a Novel Recognition Mechanism for Viral Transcriptional Regulatory Sequences. Frontiers in Chemistry. 8. 624765–624765. 51 indexed citations
2.
Kang, Sisi, Mei Yang, Suhua He, et al.. (2021). A SARS-CoV-2 antibody curbs viral nucleocapsid protein-induced complement hyperactivation. Nature Communications. 12(1). 2697–2697. 59 indexed citations
3.
Chen, Xiaoxue, Zhechong Zhou, Chunliu Huang, et al.. (2021). Crystal Structures of Bat and Human Coronavirus ORF8 Protein Ig-Like Domain Provide Insights Into the Diversity of Immune Responses. Frontiers in Immunology. 12. 807134–807134. 12 indexed citations
4.
Zhou, Ziliang, Chunliu Huang, Zhechong Zhou, et al.. (2021). Structural insight reveals SARS-CoV-2 ORF7a as an immunomodulating factor for human CD14+ monocytes. iScience. 24(3). 102187–102187. 83 indexed citations
5.
Kang, Sisi, Mei Yang, Zhongsi Hong, et al.. (2020). Crystal structure of SARS-CoV-2 nucleocapsid protein RNA binding domain reveals potential unique drug targeting sites. Acta Pharmaceutica Sinica B. 10(7). 1228–1238. 449 indexed citations breakdown →
6.
Zhou, Ziliang, Chunliu Huang, Zhechong Zhou, et al.. (2020). Structural Insight  Reveals SARS-CoV-2 Orf7a as an Immunomodulating Factor for Human CD14+ Monocytes. SSRN Electronic Journal. 1 indexed citations
7.
Li, Yujie, Yu-Lu Cao, Jian-Xiong Feng, et al.. (2019). Structural insights of human mitofusin-2 into mitochondrial fusion and CMT2A onset. Nature Communications. 10(1). 4914–4914. 119 indexed citations
8.
Kang, Sisi, Zhuo Wang, Bin Li, et al.. (2019). Anti-tumor effects of resveratrol on malignant melanoma is associated with promoter demethylation of RUNX3 gene.. PubMed. 74(3). 163–167. 5 indexed citations
9.
Kang, Sisi, et al.. (2013). Efficacy of palonosetron for the prevention of postoperative nausea and vomiting: a randomized, double-blinded, placebo-controlled trial. British Journal of Anaesthesia. 112(3). 485–490. 23 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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