Daniel Dai
Impact in
- Structural Biology top 10%
- Advanced Electron Microscopy Techniques and Applications
- Cell Biology top 10%
- Microtubule and mitosis dynamics
Papers in
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- Microtubule and mitosis dynamics 4
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- Advanced Electron Microscopy Techniques and Applications 2
- Co-authors
- Khanh Huy Bui (8 shared papers)Muneyoshi Ichikawa (5 shared papers)Shintaroh Kubo (5 shared papers)Katya Peri (5 shared papers)Ahmad Abdelzaher Zaki Khalifa (2 shared papers)Javier Vargas (2 shared papers)Corbin Steven Black (6 shared papers)Shun Kai Yang (4 shared papers)
- Journals
- eLife (3 papers)PLANT PHYSIOLOGY (1 paper)Journal of Biological Chemistry (1 paper)Proceedings of the National Academy of Sciences (1 paper)Communications Chemistry (1 paper)
- Partner nations
- CanadaJapanUnited States
In The Last Decade
Daniel Dai
11 papers receiving 289 citations
Peers
Comparison fields: 5 of 67
- Structural Biology 30
- Cell Biology 130
- Genetics 92
- Molecular Biology 182
- Cellular and Molecular Neuroscience 30
Countries citing papers authored by Daniel Dai
This map shows the geographic impact of Daniel 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 Daniel Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Dai more than expected).
Fields of papers citing papers by Daniel Dai
This network shows the impact of papers produced by Daniel 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 Daniel Dai. The network helps show where Daniel Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel 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
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 122 | |
| 2 | 2019 | 61 | |
| 3 | 2021 | 36 | |
| 4 | 2020 | 27 | |
| 5 | Programming Pig: Dataflow Scripting with Hadoop | 2016 | 12 |
| 6 | 2023 | 10 | |
| 7 | 2024 | 6 | |
| 8 | 2024 | 5 | |
| 9 | 2021 | 5 | |
| 10 | 2021 | 5 | |
| 11 | 2023 | 3 |
About Daniel Dai
Daniel Dai is a scholar working on Cell Biology, Structural Biology, Molecular Biology, Genetics and Biophysics, having authored 11 papers that have together received 292 indexed citations. Recurring topics across this work include Protist diversity and phylogeny (6 papers), Photosynthetic Processes and Mechanisms (4 papers), Microtubule and mitosis dynamics (4 papers), Genetic and Kidney Cyst Diseases (3 papers), Advanced Electron Microscopy Techniques and Applications (2 papers), Ubiquitin and proteasome pathways (2 papers), Mass Spectrometry Techniques and Applications (1 paper) and Advanced Proteomics Techniques and Applications (1 paper). The work is most often cited by research in Structural Biology (30 citations), Cell Biology (130 citations), Genetics (92 citations), Molecular Biology (182 citations) and Cellular and Molecular Neuroscience (30 citations). Daniel Dai has collaborated with scholars based in Canada, Japan and United States. Frequent co-authors include Khanh Huy Bui, Muneyoshi Ichikawa, Shintaroh Kubo, Katya Peri, Ahmad Abdelzaher Zaki Khalifa, Javier Vargas, Corbin Steven Black, Shun Kai Yang, Thomas S. McAlear and Simon Veyron. Their work appears in journals such as eLife, PLANT PHYSIOLOGY, Journal of Biological Chemistry, Proceedings of the National Academy of Sciences and Communications Chemistry.
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.