Wei Dai
Impact in
- Molecular Medicine top 2%
- Antibiotic Resistance in Bacteria
- Endocrinology top 5%
- Enterobacteriaceae and Cronobacter Research
- Vibrio bacteria research studies
Papers in
-
- MicroRNA in disease regulation 3
-
- Nutritional Studies and Diet 3
- Co-authors
- Liping Zhang (5 shared papers)Xiaojiao Zhang (3 shared papers)Shifeng Huang (3 shared papers)István Tóth (4 shared papers)Reshma J. Nevagi (3 shared papers)Shunping He (2 shared papers)Ju Cao (2 shared papers)Kainan Wu (4 shared papers)
- Journals
- PLoS ONE (4 papers)Frontiers in Immunology (2 papers)Public Health Nutrition (2 papers)Infection Genetics and Evolution (2 papers)Theoretical and Applied Genetics (2 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Wei Dai
65 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 145
- Molecular Medicine 180
- Endocrinology 124
- Obstetrics and Gynecology 83
- Applied Microbiology and Biotechnology 20
- Cancer Research 91
Countries citing papers authored by Wei Dai
This map shows the geographic impact of Wei Dai'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 Wei Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Dai more than expected).
Fields of papers citing papers by Wei Dai
This network shows the impact of papers produced by Wei Dai. 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 Wei Dai. The network helps show where Wei Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Wei Dai, 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 70 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 84 | |
| 2 | 2017 | 77 | |
| 3 | 2016 | 60 | |
| 4 | 2017 | 56 | |
| 5 | 2012 | 50 | |
| 6 | 2015 | 49 | |
| 7 | 2012 | 44 | |
| 8 | 2017 | 44 | |
| 9 | 2017 | 40 | |
| 10 | 2015 | 37 | |
| 11 | 2015 | 36 | |
| 12 | 2015 | 29 | |
| 13 | 2019 | 28 | |
| 14 | 2019 | 26 | |
| 15 | 2022 | 26 | |
| 16 | 2018 | 26 | |
| 17 | 2017 | 26 | |
| 18 | 2015 | 24 | |
| 19 | 2014 | 24 | |
| 20 | 2017 | 22 |
About Wei Dai
Wei Dai is a scholar working on Cancer Research, Public Health, Environmental and Occupational Health, Molecular Biology, Oncology and Epidemiology, having authored 70 papers that have together received 1.1k indexed citations. Recurring topics across this work include Antibiotic Resistance in Bacteria (7 papers), Marine and coastal plant biology (6 papers), Nutritional Studies and Diet (3 papers), Energy, Environment, Economic Growth (3 papers), Health disparities and outcomes (3 papers), Planetary Science and Exploration (3 papers), MicroRNA in disease regulation (3 papers) and Antibiotics Pharmacokinetics and Efficacy (3 papers). The work is most often cited by research in Molecular Medicine (180 citations), Endocrinology (124 citations), Obstetrics and Gynecology (83 citations), Applied Microbiology and Biotechnology (20 citations) and Cancer Research (91 citations). Wei Dai has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Liping Zhang, Xiaojiao Zhang, Shifeng Huang, István Tóth, Reshma J. Nevagi, Shunping He, Ju Cao, Kainan Wu, Lingquan Kong and Yutuan Wu. Their work appears in journals such as PLoS ONE, Frontiers in Immunology, Public Health Nutrition, Infection Genetics and Evolution and Theoretical and Applied Genetics.
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.