Fang‐Xiang Wu
- Computational Theory and Mathematics top 0.1%
- Computational Drug Discovery Methods 79
- Cancer Research top 0.5%
- Cancer-related molecular mechanisms research 39
- Molecular Biology top 0.5%
- Bioinformatics and Genomic Networks 171
- Machine Learning in Bioinformatics 98
- Gene expression and cancer classification 86
- Gene Regulatory Network Analysis 74
- Protein Structure and Dynamics 43
- Neurology top 1%
- Health Information Management top 0.5%
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- Advanced Proteomics Techniques and Applications 34
- Co-authors
- Jianxin WangYi PanMin LiXiujuan LeiYaohang LiYu TangJin LiuWenjun Zhang
- Journals
- Nucleic Acids Research (1 paper)SHILAP Revista de lepidopterología (1 paper)Bioinformatics (20 papers)
- Partner nations
- CanadaChinaUnited States
In The Last Decade
Fang‐Xiang Wu
426 papers receiving 11.9k citations
Hit Papers
Peers
Comparison fields: 5 of 202
- Computational Theory and Mathematics 2.6k
- Cancer Research 2.2k
- Molecular Biology 8.0k
- Neurology 794
- Health Information Management 266
Countries citing papers authored by Fang‐Xiang Wu
This map shows the geographic impact of Fang‐Xiang 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 Fang‐Xiang Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fang‐Xiang Wu more than expected).
Fields of papers citing papers by Fang‐Xiang Wu
This network shows the impact of papers produced by Fang‐Xiang 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 Fang‐Xiang Wu. The network helps show where Fang‐Xiang Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Fang‐Xiang 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
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 7 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 5 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 7 | |
| 7 | 2023 | 5 | |
| 8 | 2023 | 10 | |
| 9 | 2023 | 3 | |
| 10 | 2023 | 2 | |
| 11 | 2022 | 10 | |
| 12 | 2022 | 11 | |
| 13 | 2021 | 65 | |
| 14 | 2021 | 32 | |
| 15 | 2020 | 4 | |
| 16 | 2020 | 9 | |
| 17 | 2019 | 9 | |
| 18 | 2017 | 13 | |
| 19 | 2014 | 7 | |
| 20 | 2004 | 3 |
About Fang‐Xiang Wu
Fang‐Xiang Wu is a scholar working on Molecular Biology, Computational Theory and Mathematics and Cancer Research, having authored 443 papers that have together received 12.2k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (171 papers), Machine Learning in Bioinformatics (98 papers), Gene expression and cancer classification (86 papers), Computational Drug Discovery Methods (79 papers), Gene Regulatory Network Analysis (74 papers), Protein Structure and Dynamics (43 papers), Cancer-related molecular mechanisms research (39 papers) and Advanced Proteomics Techniques and Applications (34 papers). The work is most often cited by research in Computational Theory and Mathematics (2.6k citations), Cancer Research (2.2k citations) and Molecular Biology (8.0k citations). Fang‐Xiang Wu has collaborated with scholars based in Canada, China and United States. Frequent co-authors include Jianxin Wang, Yi Pan, Min Li, Xiujuan Lei, Yaohang Li, Yu Tang, Jin Liu, Wenjun Zhang, Min Zeng and Wei Lan. Their work appears in journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Bioinformatics.
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.