Da Qi
Impact in
- Spectroscopy top 10%
- Advanced Proteomics Techniques and Applications
- Mass Spectrometry Techniques and Applications
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- Barrier Structure and Function Studies
Papers in
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- Metabolomics and Mass Spectrometry Studies 7
- Heat shock proteins research 2
- Machine Learning in Bioinformatics 2
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- Mass Spectrometry Techniques and Applications 9
- Advanced Proteomics Techniques and Applications 7
- Co-authors
- Andrew R. Jones (10 shared papers)Chengshi Quan (12 shared papers)Huinan Qu (12 shared papers)Yuan Dong (10 shared papers)Xinqi Wang (5 shared papers)Wenhong Xu (5 shared papers)Yantong Guo (4 shared papers)Peiye Song (4 shared papers)
- Journals
- PROTEOMICS (4 papers)Journal of Experimental & Clinical Cancer Research (3 papers)Molecular & Cellular Proteomics (2 papers)Cellular Signalling (2 papers)Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics (1 paper)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Da Qi
34 papers receiving 698 citations
Peers
Comparison fields: 5 of 92
- Spectroscopy 142
- Neurology 49
- Molecular Biology 416
- Cancer Research 80
- Aquatic Science 22
Countries citing papers authored by Da Qi
This map shows the geographic impact of Da Qi'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 Da Qi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Da Qi more than expected).
Fields of papers citing papers by Da Qi
This network shows the impact of papers produced by Da Qi. 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 Da Qi. The network helps show where Da Qi may publish in the future.
Co-authors
The 25 scholars most cited alongside Da Qi, 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 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 108 | |
| 2 | 2013 | 48 | |
| 3 | 2014 | 46 | |
| 4 | 2019 | 46 | |
| 5 | 2019 | 46 | |
| 6 | 2019 | 45 | |
| 7 | 2012 | 44 | |
| 8 | 2020 | 44 | |
| 9 | 2019 | 28 | |
| 10 | 2010 | 26 | |
| 11 | 2018 | 23 | |
| 12 | 2010 | 23 | |
| 13 | 2023 | 23 | |
| 14 | 2018 | 21 | |
| 15 | 2017 | 20 | |
| 16 | 2018 | 20 | |
| 17 | 2021 | 16 | |
| 18 | 2024 | 13 | |
| 19 | 2022 | 13 | |
| 20 | 2014 | 7 |
About Da Qi
Da Qi is a scholar working on Molecular Biology, Spectroscopy, Pulmonary and Respiratory Medicine, Neurology and Epidemiology, having authored 35 papers that have together received 701 indexed citations. Recurring topics across this work include Mass Spectrometry Techniques and Applications (9 papers), Advanced Proteomics Techniques and Applications (7 papers), Metabolomics and Mass Spectrometry Studies (7 papers), Barrier Structure and Function Studies (4 papers), Ferroptosis and cancer prognosis (3 papers), Heat shock proteins research (2 papers), Cancer, Lipids, and Metabolism (2 papers) and Machine Learning in Bioinformatics (2 papers). The work is most often cited by research in Spectroscopy (142 citations), Neurology (49 citations), Molecular Biology (416 citations), Cancer Research (80 citations) and Aquatic Science (22 citations). Da Qi has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Andrew R. Jones, Chengshi Quan, Huinan Qu, Yuan Dong, Xinqi Wang, Wenhong Xu, Yantong Guo, Peiye Song, Yiyang Jia and Xiangshu Jin. Their work appears in journals such as PROTEOMICS, Journal of Experimental & Clinical Cancer Research, Molecular & Cellular Proteomics, Cellular Signalling and Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics.
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.