Haibo Wu

146 total papers · 4.2k total citations
100 papers, 2.5k citations indexed

About

Haibo Wu is a scholar working on Molecular Biology, Immunology and Infectious Diseases. According to data from OpenAlex, Haibo Wu has authored 100 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Molecular Biology, 18 papers in Immunology and 16 papers in Infectious Diseases. Recurrent topics in Haibo Wu's work include SARS-CoV-2 and COVID-19 Research (12 papers), MicroRNA in disease regulation (9 papers) and CRISPR and Genetic Engineering (7 papers). Haibo Wu is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (12 papers), MicroRNA in disease regulation (9 papers) and CRISPR and Genetic Engineering (7 papers). Haibo Wu collaborates with scholars based in China, Germany and Egypt. Haibo Wu's co-authors include Beibei Fu, Jiamin Zhao, Jingcheng Zhang, Xiaoyuan Lin, Wei Peng, Weiwei Xue, Yongsheng Wang, Songna Yin, Yong Zhang and Na Xing and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Haibo Wu

91 papers receiving 2.5k citations

Author Peers

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

Author Last Decade Papers Cites
Haibo Wu 1.2k 469 272 264 264 100 2.5k
Li Han 1.8k 1.5× 516 1.1× 237 0.9× 383 1.5× 349 1.3× 115 3.7k
Jing Bi 978 0.8× 493 1.1× 143 0.5× 349 1.3× 310 1.2× 101 2.6k
Yeji Kim 1.4k 1.2× 202 0.4× 248 0.9× 205 0.8× 241 0.9× 71 2.5k
Yuan‐Man Hsu 1.3k 1.1× 190 0.4× 330 1.2× 106 0.4× 353 1.3× 118 3.4k
Xin Jiang 1.9k 1.6× 502 1.1× 425 1.6× 237 0.9× 361 1.4× 136 3.3k
Yuan Lin 1.9k 1.6× 285 0.6× 282 1.0× 213 0.8× 537 2.0× 138 3.4k
Christiane V. Löhr 1.2k 1.0× 184 0.4× 356 1.3× 307 1.2× 337 1.3× 142 3.1k
Yujiong Wang 1.2k 1.0× 342 0.7× 261 1.0× 144 0.5× 326 1.2× 110 2.8k
Lara Gibellini 1.7k 1.5× 461 1.0× 314 1.2× 110 0.4× 663 2.5× 97 3.9k
Xu Zhang 1.6k 1.3× 390 0.8× 317 1.2× 188 0.7× 649 2.5× 98 3.2k

Countries citing papers authored by Haibo Wu

Since Specialization
Citations

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

Fields of papers citing papers by Haibo Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haibo Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Haibo Wu. A scholar is included among the top collaborators of Haibo Wu 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 Haibo Wu. Haibo Wu 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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