Haozhou Tan

40 total papers · 1.2k total citations
25 papers, 670 citations indexed

About

Haozhou Tan is a scholar working on Infectious Diseases, Molecular Biology and Computational Theory and Mathematics. According to data from OpenAlex, Haozhou Tan has authored 25 papers receiving a total of 670 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Infectious Diseases, 13 papers in Molecular Biology and 8 papers in Computational Theory and Mathematics. Recurrent topics in Haozhou Tan's work include SARS-CoV-2 and COVID-19 Research (14 papers), Computational Drug Discovery Methods (8 papers) and Viral Infections and Immunology Research (6 papers). Haozhou Tan is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (14 papers), Computational Drug Discovery Methods (8 papers) and Viral Infections and Immunology Research (6 papers). Haozhou Tan collaborates with scholars based in United States, Greece and China. Haozhou Tan's co-authors include Jun Wang, Yanmei Hu, Bin Tan, Chunlong Ma, Prakash D. Jadhav, Yu Chen, Maura V. Gongora, Xufang Deng, Lian Jacobs and Xiujun Zhang and has published in prestigious journals such as Science, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Haozhou Tan

22 papers receiving 667 citations

Hit Papers

Naturally Occurring Mutat... 2023 2026 2024 2023 2024 50 100 150

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Haozhou Tan 424 337 219 131 58 25 670
Kristina Lanko 300 0.7× 233 0.7× 216 1.0× 132 1.0× 51 0.9× 14 586
Justin Shields 351 0.8× 287 0.9× 249 1.1× 107 0.8× 92 1.6× 12 737
Sakshi Tomar 475 1.1× 303 0.9× 243 1.1× 110 0.8× 42 0.7× 21 777
Carly Huitema 408 1.0× 298 0.9× 204 0.9× 119 0.9× 36 0.6× 12 765
Lucía Barrado-Gil 320 0.8× 158 0.5× 163 0.7× 75 0.6× 67 1.2× 16 738
Amgad M. Rabie 234 0.6× 157 0.5× 198 0.9× 143 1.1× 76 1.3× 28 589
Mikołaj Żmudziński 393 0.9× 323 1.0× 278 1.3× 112 0.9× 26 0.4× 9 690
María Luisa Serrano 278 0.7× 175 0.5× 182 0.8× 107 0.8× 63 1.1× 32 741
Daniel Brian Nichols 338 0.8× 129 0.4× 212 1.0× 96 0.7× 130 2.2× 18 698
Luqing Shang 207 0.5× 118 0.4× 319 1.5× 114 0.9× 53 0.9× 27 684

Countries citing papers authored by Haozhou Tan

Since Specialization
Citations

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

Fields of papers citing papers by Haozhou Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haozhou Tan

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

All Works

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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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