Jun Dai
Impact in
- Food Science top 2%
- Proteins in Food Systems
- Polysaccharides Composition and Applications
- Fermentation and Sensory Analysis
- Biotechnology top 2%
Papers in
-
- Genomics and Phylogenetic Studies 39
- Microbial Metabolic Engineering and Bioproduction 16
- Fungal and yeast genetics research 8
- Food Science 29
- Fermentation and Sensory Analysis 11
- Proteins in Food Systems 8
- Co-authors
- Chengxiang Fang (29 shared papers)Shangwei Chen (8 shared papers)Song Zhu (5 shared papers)Jian Tang (3 shared papers)Fang Peng (14 shared papers)Yan Wu (1 shared paper)Hongping Yin (1 shared paper)Min Wang (1 shared paper)
- Journals
- INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY (22 papers)Antonie van Leeuwenhoek (5 papers)Food Hydrocolloids (4 papers)Marine Drugs (3 papers)Food Research International (3 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Jun Dai
136 papers receiving 2.9k citations
Peers
Comparison fields: 5 of 133
- Food Science 533
- Biotechnology 211
- Ecology 591
- Molecular Biology 1.5k
- Plant Science 753
Countries citing papers authored by Jun Dai
This map shows the geographic impact of Jun 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 Jun Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Dai more than expected).
Fields of papers citing papers by Jun Dai
This network shows the impact of papers produced by Jun 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 Jun Dai. The network helps show where Jun Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun 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 147 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 339 | |
| 2 | 2014 | 103 | |
| 3 | 2022 | 98 | |
| 4 | 2020 | 84 | |
| 5 | 2011 | 77 | |
| 6 | 2011 | 76 | |
| 7 | 2009 | 63 | |
| 8 | 2008 | 53 | |
| 9 | 2011 | 51 | |
| 10 | 2008 | 51 | |
| 11 | 2021 | 48 | |
| 12 | 2022 | 46 | |
| 13 | 2009 | 43 | |
| 14 | 2014 | 42 | |
| 15 | 2011 | 41 | |
| 16 | 2023 | 40 | |
| 17 | 2014 | 39 | |
| 18 | 2010 | 38 | |
| 19 | 2020 | 37 | |
| 20 | 2022 | 37 |
About Jun Dai
Jun Dai is a scholar working on Molecular Biology, Food Science, Plant Science, Ecology and Pharmacology, having authored 147 papers that have together received 2.9k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (39 papers), Microbial Community Ecology and Physiology (24 papers), Microbial Metabolic Engineering and Bioproduction (16 papers), Biological and pharmacological studies of plants (13 papers), Fermentation and Sensory Analysis (11 papers), Proteins in Food Systems (8 papers), Fungal and yeast genetics research (8 papers) and Phytochemicals and Antioxidant Activities (7 papers). The work is most often cited by research in Food Science (533 citations), Biotechnology (211 citations), Ecology (591 citations), Molecular Biology (1.5k citations) and Plant Science (753 citations). Jun Dai has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Chengxiang Fang, Shangwei Chen, Song Zhu, Jian Tang, Fang Peng, Yan Wu, Hongping Yin, Min Wang, Yali Tang and Fan Jiang. Their work appears in journals such as INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY, Antonie van Leeuwenhoek, Food Hydrocolloids, Marine Drugs and Food Research International.
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.