Dingfeng Wu
Impact in
-
- Computational Drug Discovery Methods
- Infectious Diseases top 10%
- COVID-19 Clinical Research Studies
Papers in
-
- Gut microbiota and health 14
- Bioinformatics and Genomic Networks 5
- Metabolomics and Mass Spectrometry Studies 4
- Biochemical and Structural Characterization 3
- Epidemiology 12
- Liver Disease Diagnosis and Treatment 7
- Co-authors
- Ruixin Zhu (38 shared papers)Lixin Zhu (23 shared papers)Na Jiao (17 shared papers)Kailin Tang (7 shared papers)Zhiwei Cao (6 shared papers)Tianyi Qiu (8 shared papers)Ping Lan (7 shared papers)Sijing Cheng (4 shared papers)
- Journals
- The FASEB Journal (4 papers)Briefings in Bioinformatics (4 papers)Gut Microbes (3 papers)Frontiers in Pharmacology (3 papers)Nature Communications (3 papers)
- Partner nations
- ChinaUnited StatesItaly
In The Last Decade
Dingfeng Wu
54 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 112
- Computational Theory and Mathematics 172
- Infectious Diseases 167
- Molecular Biology 642
- Biological Psychiatry 18
- Pharmacology 52
Countries citing papers authored by Dingfeng Wu
This map shows the geographic impact of Dingfeng 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 Dingfeng Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dingfeng Wu more than expected).
Fields of papers citing papers by Dingfeng Wu
This network shows the impact of papers produced by Dingfeng 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 Dingfeng Wu. The network helps show where Dingfeng Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Dingfeng 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 57 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 170 | |
| 2 | 2020 | 121 | |
| 3 | 2015 | 115 | |
| 4 | 2020 | 73 | |
| 5 | 2014 | 50 | |
| 6 | 2018 | 48 | |
| 7 | 2015 | 43 | |
| 8 | 2015 | 42 | |
| 9 | 2016 | 33 | |
| 10 | 2022 | 30 | |
| 11 | 2019 | 30 | |
| 12 | 2012 | 27 | |
| 13 | 2023 | 27 | |
| 14 | 2018 | 26 | |
| 15 | 2021 | 22 | |
| 16 | 2016 | 20 | |
| 17 | 2022 | 19 | |
| 18 | 2023 | 19 | |
| 19 | 2024 | 18 | |
| 20 | 2016 | 18 |
About Dingfeng Wu
Dingfeng Wu is a scholar working on Molecular Biology, Epidemiology, Computational Theory and Mathematics, Oncology and Infectious Diseases, having authored 57 papers that have together received 1.1k indexed citations. Recurring topics across this work include Gut microbiota and health (14 papers), Computational Drug Discovery Methods (9 papers), Liver Disease Diagnosis and Treatment (7 papers), Bioinformatics and Genomic Networks (5 papers), Metabolomics and Mass Spectrometry Studies (4 papers), Biochemical and Structural Characterization (3 papers), COVID-19 Clinical Research Studies (3 papers) and Inflammatory Bowel Disease (3 papers). The work is most often cited by research in Computational Theory and Mathematics (172 citations), Infectious Diseases (167 citations), Molecular Biology (642 citations), Biological Psychiatry (18 citations) and Pharmacology (52 citations). Dingfeng Wu has collaborated with scholars based in China, United States and Italy. Frequent co-authors include Ruixin Zhu, Lixin Zhu, Na Jiao, Kailin Tang, Zhiwei Cao, Tianyi Qiu, Ping Lan, Sijing Cheng, Yida Zhang and Yichen Li. Their work appears in journals such as The FASEB Journal, Briefings in Bioinformatics, Gut Microbes, Frontiers in Pharmacology and Nature Communications.
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.