Binli Mao

456 total citations · 1 hit paper
9 papers, 317 citations indexed

About

Binli Mao is a scholar working on Molecular Biology, Infectious Diseases and Epidemiology. According to data from OpenAlex, Binli Mao has authored 9 papers receiving a total of 317 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Infectious Diseases and 3 papers in Epidemiology. Recurrent topics in Binli Mao's work include SARS-CoV-2 and COVID-19 Research (3 papers), Autophagy in Disease and Therapy (2 papers) and Extracellular vesicles in disease (2 papers). Binli Mao is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (3 papers), Autophagy in Disease and Therapy (2 papers) and Extracellular vesicles in disease (2 papers). Binli Mao collaborates with scholars based in China, Germany and South Korea. Binli Mao's co-authors include Zhenyu Zhao, Yong Lin, Kefeng Lu, Huihui Li, Hao Sun, Rongjuan Pei, Yabin Zhang, Ailong Huang, Mengji Lu and Yingying Deng and has published in prestigious journals such as Journal of Controlled Release, Frontiers in Immunology and Virus Research.

In The Last Decade

Binli Mao

9 papers receiving 310 citations

Hit Papers

The SARS-CoV-2 protein ORF3a inhibits fusion of autophago... 2021 2026 2022 2024 2021 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Binli Mao China 7 136 115 107 55 40 9 317
Ansgar F. Stenzel Germany 2 219 1.6× 56 0.5× 160 1.5× 82 1.5× 11 0.3× 2 351
Avery Peace United States 3 222 1.6× 57 0.5× 162 1.5× 84 1.5× 11 0.3× 5 358
Katherine Travisano United States 2 151 1.1× 43 0.4× 119 1.1× 49 0.9× 10 0.3× 3 261
Oded Danziger Israel 8 253 1.9× 60 0.5× 208 1.9× 119 2.2× 14 0.3× 9 464
Inna Ricardo-Lax United States 8 234 1.7× 95 0.8× 264 2.5× 91 1.7× 12 0.3× 12 535
Lawrence G. Welch United Kingdom 4 240 1.8× 35 0.3× 139 1.3× 48 0.9× 13 0.3× 6 392
Elisabeth Braun Germany 5 131 1.0× 44 0.4× 90 0.8× 72 1.3× 4 0.1× 7 286
Krishnan Harinivas Harshan India 8 100 0.7× 33 0.3× 76 0.7× 41 0.7× 10 0.3× 20 201
Inés Ripa Spain 10 66 0.5× 54 0.5× 158 1.5× 32 0.6× 5 0.1× 17 277
Jinxin Ou China 6 79 0.6× 47 0.4× 172 1.6× 33 0.6× 8 0.2× 6 303

Countries citing papers authored by Binli Mao

Since Specialization
Citations

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

Fields of papers citing papers by Binli Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Binli Mao

This figure shows the co-authorship network connecting the top 25 collaborators of Binli Mao. A scholar is included among the top collaborators of Binli Mao 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 Binli Mao. Binli Mao 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.
Khan, Muhammad Naveed, Binli Mao, Juan Hu, et al.. (2024). Tumor-associated macrophages and CD8+ T cells: dual players in the pathogenesis of HBV-related HCC. Frontiers in Immunology. 15. 1472430–1472430. 15 indexed citations
2.
Mao, Binli, Vu Thuy Khanh Le‐Trilling, Jie Hu, et al.. (2024). Diphyllin elicits a doubled-pronged attack on the entry of SARS-CoV-2 by inhibiting cathepsin L and furin. Virus Research. 350. 199485–199485. 1 indexed citations
3.
Rehman, Adeel ur, Hanyang Liu, Binli Mao, et al.. (2024). Enhancing antitumor immunity and achieving tumor eradication with IL11RA mRNA immunotherapy. International Immunopharmacology. 134. 112205–112205. 9 indexed citations
4.
Mao, Binli, Shunyao Wang, Jinjun Guo, et al.. (2024). Enhanced delivery of CRISPR/Cas9 system based on biomimetic nanoparticles for hepatitis B virus therapy. Journal of Controlled Release. 374. 293–311. 9 indexed citations
5.
Mao, Binli, Vu Thuy Khanh Le‐Trilling, Kai Wang, et al.. (2022). Obatoclax inhibits SARS-CoV-2 entry by altered endosomal acidification and impaired cathepsin and furin activity in vitro. Emerging Microbes & Infections. 11(1). 483–497. 18 indexed citations
6.
Zhang, Yabin, Hao Sun, Rongjuan Pei, et al.. (2021). The SARS-CoV-2 protein ORF3a inhibits fusion of autophagosomes with lysosomes. Cell Discovery. 7(1). 31–31. 170 indexed citations breakdown →
7.
Zheng, Jiaxin, Yingying Deng, Zhenyu Zhao, et al.. (2021). Characterization of SARS-CoV-2-specific humoral immunity and its potential applications and therapeutic prospects. Cellular and Molecular Immunology. 19(2). 150–157. 41 indexed citations
8.
Zhao, Zhenyu, Kefeng Lu, Binli Mao, et al.. (2021). The interplay between emerging human coronavirus infections and autophagy. Emerging Microbes & Infections. 10(1). 196–205. 48 indexed citations
9.
Mao, Binli, Zhuo Wang, Quanxin Long, et al.. (2020). Difluoromethylornithine, a Decarboxylase 1 Inhibitor, Suppresses Hepatitis B Virus Replication by Reducing HBc Protein Levels. Frontiers in Cellular and Infection Microbiology. 10. 158–158. 6 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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