Su‐Jun Li
Impact in
- Spectroscopy top 5%
- Advanced Proteomics Techniques and Applications
- Mass Spectrometry Techniques and Applications
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- Metabolomics and Mass Spectrometry Studies
- Glycosylation and Glycoproteins Research
- Ubiquitin and proteasome pathways
- Machine Learning in Bioinformatics
Papers in
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- Metabolomics and Mass Spectrometry Studies 4
- vaccines and immunoinformatics approaches 2
- Ubiquitin and proteasome pathways 2
- Machine Learning in Bioinformatics 1
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- Advanced Proteomics Techniques and Applications 8
- Mass Spectrometry Techniques and Applications 7
- Co-authors
- Rong Zeng (9 shared papers)Qi‐Chang Xia (6 shared papers)Hu Zhou (6 shared papers)Jiarui Wu (5 shared papers)Quanhu Sheng (6 shared papers)Jie Dai (4 shared papers)Xiao-Sheng Jiang (3 shared papers)Yixue Li (4 shared papers)
- Journals
- Molecular & Cellular Proteomics (4 papers)Journal of Proteome Research (3 papers)Rapid Communications in Mass Spectrometry (2 papers)Molecular Diversity (1 paper)Cell Research (1 paper)
- Partner nations
- ChinaUnited StatesNepal
In The Last Decade
Su‐Jun Li
16 papers receiving 593 citations
Peers
Comparison fields: 5 of 74
- Spectroscopy 231
- Molecular Biology 386
- Cell Biology 65
- Cancer Research 54
- Oncology 75
Countries citing papers authored by Su‐Jun Li
This map shows the geographic impact of Su‐Jun Li'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 Su‐Jun Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Su‐Jun Li more than expected).
Fields of papers citing papers by Su‐Jun Li
This network shows the impact of papers produced by Su‐Jun Li. 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 Su‐Jun Li. The network helps show where Su‐Jun Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Su‐Jun Li, 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 | 2005 | 90 | |
| 2 | 2005 | 69 | |
| 3 | 2005 | 66 | |
| 4 | 2004 | 60 | |
| 5 | 2008 | 56 | |
| 6 | 2007 | 53 | |
| 7 | 2005 | 37 | |
| 8 | 2009 | 34 | |
| 9 | 2005 | 31 | |
| 10 | 2010 | 28 | |
| 11 | 2009 | 26 | |
| 12 | 2005 | 21 | |
| 13 | 2009 | 18 | |
| 14 | 2008 | 10 | |
| 15 | 2018 | 1 | |
| 16 | 2016 | 1 |
About Su‐Jun Li
Su‐Jun Li is a scholar working on Molecular Biology, Spectroscopy, Oncology, Cell Biology and Cancer Research, having authored 16 papers that have together received 601 indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (8 papers), Mass Spectrometry Techniques and Applications (7 papers), Metabolomics and Mass Spectrometry Studies (4 papers), Endoplasmic Reticulum Stress and Disease (2 papers), vaccines and immunoinformatics approaches (2 papers), Ubiquitin and proteasome pathways (2 papers), Pancreatic function and diabetes (1 paper) and Machine Learning in Bioinformatics (1 paper). The work is most often cited by research in Spectroscopy (231 citations), Molecular Biology (386 citations), Cell Biology (65 citations), Cancer Research (54 citations) and Oncology (75 citations). Su‐Jun Li has collaborated with scholars based in China, United States and Nepal. Frequent co-authors include Rong Zeng, Qi‐Chang Xia, Hu Zhou, Jiarui Wu, Quanhu Sheng, Jie Dai, Xiao-Sheng Jiang, Yixue Li, Jie Dai and Liu-Ya Tang. Their work appears in journals such as Molecular & Cellular Proteomics, Journal of Proteome Research, Rapid Communications in Mass Spectrometry, Molecular Diversity and Cell Research.
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.