Kejiang Lin
Impact in
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- Computational Drug Discovery Methods
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- Bacterial biofilms and quorum sensing
- Angiogenesis and VEGF in Cancer
- Protein Structure and Dynamics
- Metabolomics and Mass Spectrometry Studies
Papers in
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- Cancer therapeutics and mechanisms 4
- Receptor Mechanisms and Signaling 2
- Bacterial biofilms and quorum sensing 2
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- Computational Drug Discovery Methods 9
- Co-authors
- Hequan Yao (12 shared papers)Xuanyi Li (10 shared papers)Lingyi Huang (1 shared paper)Zhi-Qiang Bai (1 shared paper)Rui Xie (1 shared paper)Li‐Ping Sun (1 shared paper)Huayu Liu (1 shared paper)Likun Zhang (1 shared paper)
In The Last Decade
Kejiang Lin
32 papers receiving 471 citations
Peers
Comparison fields: 5 of 87
- Computational Theory and Mathematics 118
- Molecular Biology 254
- Toxicology 11
- Molecular Medicine 16
- Oncology 66
Countries citing papers authored by Kejiang Lin
This map shows the geographic impact of Kejiang Lin'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 Kejiang Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kejiang Lin more than expected).
Fields of papers citing papers by Kejiang Lin
This network shows the impact of papers produced by Kejiang Lin. 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 Kejiang Lin. The network helps show where Kejiang Lin may publish in the future.
Co-authors
The 25 scholars most cited alongside Kejiang Lin, 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 | 2012 | 81 | |
| 2 | 2018 | 52 | |
| 3 | 2020 | 48 | |
| 4 | 2021 | 30 | |
| 5 | 2020 | 25 | |
| 6 | 2017 | 24 | |
| 7 | 2018 | 23 | |
| 8 | 2018 | 16 | |
| 9 | 2021 | 14 | |
| 10 | 2017 | 14 | |
| 11 | 2018 | 13 | |
| 12 | 2019 | 13 | |
| 13 | 2020 | 12 | |
| 14 | 2019 | 11 | |
| 15 | 2020 | 10 | |
| 16 | 2018 | 10 | |
| 17 | 2019 | 10 | |
| 18 | 2024 | 9 | |
| 19 | 2018 | 8 | |
| 20 | 2022 | 7 |
About Kejiang Lin
Kejiang Lin is a scholar working on Molecular Biology, Computational Theory and Mathematics, Organic Chemistry, Oncology and Materials Chemistry, having authored 35 papers that have together received 476 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (9 papers), Cancer therapeutics and mechanisms (4 papers), Machine Learning in Materials Science (3 papers), Receptor Mechanisms and Signaling (2 papers), HER2/EGFR in Cancer Research (2 papers), Immunotherapy and Immune Responses (2 papers), Bacterial biofilms and quorum sensing (2 papers) and Bone health and treatments (2 papers). The work is most often cited by research in Computational Theory and Mathematics (118 citations), Molecular Biology (254 citations), Toxicology (11 citations), Molecular Medicine (16 citations) and Oncology (66 citations). Kejiang Lin has collaborated with scholars based in China, Taiwan and Macao. Frequent co-authors include Hequan Yao, Xuanyi Li, Lingyi Huang, Zhi-Qiang Bai, Rui Xie, Li‐Ping Sun, Huayu Liu, Likun Zhang, Xin Chen and Mingxiang Zhang. Their work appears in journals such as Future Medicinal Chemistry, Expert Opinion on Therapeutic Patents, Acta Biochimica et Biophysica Sinica, European Journal of Medicinal Chemistry and Bioorganic & Medicinal Chemistry Letters.
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.