Shi‐Jian Ding
Impact in
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- Cancer, Hypoxia, and Metabolism
- MicroRNA in disease regulation
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- Machine Learning in Bioinformatics
- Bioinformatics and Genomic Networks
- Metabolomics and Mass Spectrometry Studies
Papers in
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- Machine Learning in Bioinformatics 12
- Advanced biosensing and bioanalysis techniques 2
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- COVID-19 diagnosis using AI 6
- Co-authors
- Hu Zhou (2 shared papers)Yu‐Dong Cai (18 shared papers)Tao Huang (17 shared papers)Yan Li (1 shared paper)Xiao‐Xia Shao (1 shared paper)Zhao–You Tang (1 shared paper)Qi‐Chang Xia (1 shared paper)Rong Zeng (1 shared paper)
- Journals
- BioMed Research International (4 papers)PROTEOMICS (3 papers)Frontiers in Genetics (3 papers)Frontiers in Cell and Developmental Biology (2 papers)Life (2 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Shi‐Jian Ding
31 papers receiving 533 citations
Peers
Comparison fields: 5 of 85
- Cancer Research 111
- Molecular Biology 351
- Cell Biology 74
- Spectroscopy 63
- Immunology and Allergy 19
Countries citing papers authored by Shi‐Jian Ding
This map shows the geographic impact of Shi‐Jian Ding'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 Shi‐Jian Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shi‐Jian Ding more than expected).
Fields of papers citing papers by Shi‐Jian Ding
This network shows the impact of papers produced by Shi‐Jian Ding. 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 Shi‐Jian Ding. The network helps show where Shi‐Jian Ding may publish in the future.
Co-authors
The 25 scholars most cited alongside Shi‐Jian Ding, 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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 132 | |
| 2 | 2005 | 90 | |
| 3 | 2022 | 42 | |
| 4 | 2009 | 27 | |
| 5 | 2022 | 25 | |
| 6 | 2011 | 23 | |
| 7 | 2013 | 21 | |
| 8 | 2007 | 19 | |
| 9 | 2018 | 19 | |
| 10 | 2020 | 15 | |
| 11 | 2021 | 15 | |
| 12 | 2022 | 13 | |
| 13 | 2017 | 11 | |
| 14 | 2021 | 11 | |
| 15 | 2022 | 10 | |
| 16 | 2022 | 8 | |
| 17 | 2022 | 7 | |
| 18 | 2022 | 7 | |
| 19 | 2022 | 6 | |
| 20 | 2022 | 6 |
About Shi‐Jian Ding
Shi‐Jian Ding is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Cancer Research, Infectious Diseases and Immunology, having authored 31 papers that have together received 539 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (12 papers), COVID-19 diagnosis using AI (6 papers), Cancer-related molecular mechanisms research (4 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Advanced Proteomics Techniques and Applications (4 papers), MicroRNA in disease regulation (3 papers), COVID-19 Clinical Research Studies (3 papers) and Advanced biosensing and bioanalysis techniques (2 papers). The work is most often cited by research in Cancer Research (111 citations), Molecular Biology (351 citations), Cell Biology (74 citations), Spectroscopy (63 citations) and Immunology and Allergy (19 citations). Shi‐Jian Ding has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Hu Zhou, Yu‐Dong Cai, Tao Huang, Yan Li, Xiao‐Xia Shao, Zhao–You Tang, Qi‐Chang Xia, Rong Zeng, Lei Chen and Zhandong Li. Their work appears in journals such as BioMed Research International, PROTEOMICS, Frontiers in Genetics, Frontiers in Cell and Developmental Biology and Life.
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.