Peiling Cai
Impact in
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- Computational Drug Discovery Methods
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- Machine Learning in Bioinformatics
- RNA modifications and cancer
Papers in
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- Cancer Genomics and Diagnostics 6
- Oncology 9
- Colorectal Cancer Treatments and Studies 6
- Co-authors
- Hao Lin (6 shared papers)Yang Zhang (4 shared papers)Kejun Deng (3 shared papers)Ting Wang (1 shared paper)Ting Zhang (1 shared paper)Xiaolong Yu (1 shared paper)Hui Ding (1 shared paper)Jing Xie (4 shared papers)
- Journals
- Medicine (5 papers)PLoS ONE (4 papers)Frontiers in Medicine (3 papers)Frontiers in Public Health (3 papers)Frontiers in Microbiology (2 papers)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Peiling Cai
39 papers receiving 619 citations
Peiling Cai's Hit Papers
Peers
Comparison fields: 5 of 79
- Computational Theory and Mathematics 79
- Molecular Biology 267
- Cancer Research 52
- Microbiology 24
- Drug Discovery 1
Countries citing papers authored by Peiling Cai
This map shows the geographic impact of Peiling Cai'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 Peiling Cai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peiling Cai more than expected).
Fields of papers citing papers by Peiling Cai
This network shows the impact of papers produced by Peiling Cai. 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 Peiling Cai. The network helps show where Peiling Cai may publish in the future.
Co-authors
The 25 scholars most cited alongside Peiling Cai, 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 42 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 109 | |
| 2 | Deep-STP: a deep learning-based approach to predict snake toxin proteins by using word embeddings Hit paper breakdown → | 2024 | 103 |
| 3 | 2023 | 63 | |
| 4 | 2017 | 38 | |
| 5 | 2021 | 30 | |
| 6 | 2024 | 27 | |
| 7 | 2016 | 24 | |
| 8 | 2025 | 23 | |
| 9 | 2017 | 21 | |
| 10 | 2022 | 20 | |
| 11 | 2016 | 17 | |
| 12 | 2024 | 15 | |
| 13 | 2015 | 13 | |
| 14 | 2023 | 13 | |
| 15 | 2025 | 12 | |
| 16 | 2017 | 10 | |
| 17 | 2018 | 9 | |
| 18 | 2018 | 9 | |
| 19 | 2025 | 7 | |
| 20 | 2025 | 7 |
About Peiling Cai
Peiling Cai is a scholar working on Cancer Research, Oncology, Cell Biology, Molecular Biology and Anesthesiology and Pain Medicine, having authored 42 papers that have together received 634 indexed citations. Recurring topics across this work include Colorectal Cancer Treatments and Studies (6 papers), Cancer Genomics and Diagnostics (6 papers), Gut microbiota and health (3 papers), Lung Cancer Treatments and Mutations (2 papers), Impact of Technology on Adolescents (2 papers), Computational Drug Discovery Methods (2 papers), Bone Tissue Engineering Materials (2 papers) and Caveolin-1 and cellular processes (2 papers). The work is most often cited by research in Computational Theory and Mathematics (79 citations), Molecular Biology (267 citations), Cancer Research (52 citations), Microbiology (24 citations) and Drug Discovery (1 citation). Peiling Cai has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Hao Lin, Yang Zhang, Kejun Deng, Ting Wang, Ting Zhang, Xiaolong Yu, Hui Ding, Jing Xie, Hasan Zulfiqar and Xiang Chen. Their work appears in journals such as Medicine, PLoS ONE, Frontiers in Medicine, Frontiers in Public Health and Frontiers in Microbiology.
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.