Zikai Wu
Impact in
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- Computational Drug Discovery Methods
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- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- Immune Response and Inflammation
Papers in
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- Complex Network Analysis Techniques 10
- Opinion Dynamics and Social Influence 6
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- Computational Drug Discovery Methods 6
- Co-authors
- Luonan Chen (7 shared papers)Xing‐Ming Zhao (2 shared papers)Hyun Ju Oh (1 shared paper)Matthew S. Hayden (1 shared paper)Nicole Heise (1 shared paper)Roland Michael Schmid (1 shared paper)Sankar Ghosh (2 shared papers)Ulf Klein (1 shared paper)
- Journals
- IET Systems Biology (2 papers)BMC Systems Biology (2 papers)Immunity (1 paper)Knowledge-Based Systems (1 paper)IEEE Access (1 paper)
- Partner nations
- ChinaJapanUnited States
In The Last Decade
Zikai Wu
35 papers receiving 562 citations
Peers
Comparison fields: 5 of 100
- Computational Theory and Mathematics 151
- Immunology 151
- Cancer Research 69
- Computational Mathematics 3
- Molecular Biology 256
Countries citing papers authored by Zikai Wu
This map shows the geographic impact of Zikai 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 Zikai Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zikai Wu more than expected).
Fields of papers citing papers by Zikai Wu
This network shows the impact of papers produced by Zikai 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 Zikai Wu. The network helps show where Zikai Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Zikai Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 181 | |
| 2 | 2013 | 132 | |
| 3 | 2010 | 74 | |
| 4 | 2009 | 38 | |
| 5 | 2011 | 20 | |
| 6 | 2024 | 18 | |
| 7 | 2014 | 14 | |
| 8 | 2014 | 9 | |
| 9 | 2012 | 8 | |
| 10 | 2023 | 8 | |
| 11 | 2013 | 8 | |
| 12 | 2018 | 7 | |
| 13 | 2017 | 7 | |
| 14 | 2011 | 6 | |
| 15 | 2022 | 6 | |
| 16 | 2013 | 6 | |
| 17 | 2023 | 5 | |
| 18 | 2019 | 4 | |
| 19 | 2019 | 3 | |
| 20 | 2012 | 2 |
About Zikai Wu
Zikai Wu is a scholar working on Statistical and Nonlinear Physics, Computational Theory and Mathematics, Molecular Biology, Signal Processing and Condensed Matter Physics, having authored 41 papers that have together received 575 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (10 papers), Opinion Dynamics and Social Influence (6 papers), Computational Drug Discovery Methods (6 papers), Bioinformatics and Genomic Networks (6 papers), Blind Source Separation Techniques (3 papers), Theoretical and Computational Physics (3 papers), Microbial Metabolic Engineering and Bioproduction (3 papers) and Gene Regulatory Network Analysis (2 papers). The work is most often cited by research in Computational Theory and Mathematics (151 citations), Immunology (151 citations), Cancer Research (69 citations), Computational Mathematics (3 citations) and Molecular Biology (256 citations). Zikai Wu has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Luonan Chen, Xing‐Ming Zhao, Hyun Ju Oh, Matthew S. Hayden, Nicole Heise, Roland Michael Schmid, Sankar Ghosh, Ulf Klein, Pingzhang Wang and Dev M. Bhatt. Their work appears in journals such as IET Systems Biology, BMC Systems Biology, Immunity, Knowledge-Based Systems and IEEE Access.
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.