Kai Lin
Impact in
- Molecular Biology top 5%
- TGF-β signaling in diseases
- Protein Hydrolysis and Bioactive Peptides
- Gut microbiota and health
- Cancer-related gene regulation
- Food Science top 2%
- Probiotics and Fermented Foods
Papers in
-
- Protein Hydrolysis and Bioactive Peptides 9
- TGF-β signaling in diseases 8
- Food Science 19
- Probiotics and Fermented Foods 14
- Co-authors
- Suvana S. Lam (11 shared papers)John J. Correia (8 shared papers)Bin Qin (5 shared papers)Xue Han (10 shared papers)Lanwei Zhang (30 shared papers)Benoy M. Chacko (4 shared papers)Hema Srinath (5 shared papers)Dayou Cheng (3 shared papers)
- Journals
- Journal of Biological Chemistry (8 papers)Journal of Agricultural and Food Chemistry (7 papers)Food Chemistry (6 papers)Food Research International (4 papers)International Journal of Biological Macromolecules (3 papers)
- Partner nations
- ChinaUnited StatesIndia
In The Last Decade
Kai Lin
77 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 123
- Molecular Biology 1.7k
- Food Science 421
- Cancer Research 250
- Immunology 348
- Oncology 319
Countries citing papers authored by Kai Lin
This map shows the geographic impact of Kai 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 Kai Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Lin more than expected).
Fields of papers citing papers by Kai Lin
This network shows the impact of papers produced by Kai 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 Kai Lin. The network helps show where Kai Lin may publish in the future.
Co-authors
The 25 scholars most cited alongside Kai 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 82 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2003 | 185 | |
| 2 | 2004 | 158 | |
| 3 | 1999 | 131 | |
| 4 | 2001 | 122 | |
| 5 | 2002 | 117 | |
| 6 | 2022 | 117 | |
| 7 | 2005 | 113 | |
| 8 | 2018 | 104 | |
| 9 | 2017 | 102 | |
| 10 | 2008 | 93 | |
| 11 | 2001 | 83 | |
| 12 | 2023 | 70 | |
| 13 | 2008 | 62 | |
| 14 | 2018 | 61 | |
| 15 | 2020 | 60 | |
| 16 | 1999 | 59 | |
| 17 | 2005 | 55 | |
| 18 | 2018 | 53 | |
| 19 | 2001 | 52 | |
| 20 | 2014 | 51 |
About Kai Lin
Kai Lin is a scholar working on Molecular Biology, Food Science, Materials Chemistry, Nutrition and Dietetics and Biomedical Engineering, having authored 82 papers that have together received 2.8k indexed citations. Recurring topics across this work include Probiotics and Fermented Foods (14 papers), Protein Hydrolysis and Bioactive Peptides (9 papers), TGF-β signaling in diseases (8 papers), Enzyme Structure and Function (8 papers), Cancer, Hypoxia, and Metabolism (7 papers), Infant Nutrition and Health (6 papers), Nanoplatforms for cancer theranostics (6 papers) and Amino Acid Enzymes and Metabolism (5 papers). The work is most often cited by research in Molecular Biology (1.7k citations), Food Science (421 citations), Cancer Research (250 citations), Immunology (348 citations) and Oncology (319 citations). Kai Lin has collaborated with scholars based in China, United States and India. Frequent co-authors include Suvana S. Lam, John J. Correia, Bin Qin, Xue Han, Lanwei Zhang, Benoy M. Chacko, Hema Srinath, Dayou Cheng, Zhao Ma and Huaxi Yi. Their work appears in journals such as Journal of Biological Chemistry, Journal of Agricultural and Food Chemistry, Food Chemistry, Food Research International and International Journal of Biological Macromolecules.
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.