Peiling Cai
Impact in
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- Cancer-related molecular mechanisms research
- Cancer Genomics and Diagnostics
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- Machine Learning in Bioinformatics
- RNA and protein synthesis mechanisms
- RNA modifications and cancer
- vaccines and immunoinformatics approaches
Papers in
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- Gut microbiota and health 3
- Oncology 9
- Colorectal Cancer Treatments and Studies 4
- Cancer Cells and Metastasis 2
- 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)Liping Ren (2 shared papers)Xiaolong Yu (1 shared paper)Hui Ding (1 shared paper)
- Journals
- Medicine (5 papers)PLoS ONE (4 papers)Frontiers in Public Health (3 papers)Frontiers in Medicine (3 papers)Frontiers in Endocrinology (2 papers)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Peiling Cai
34 papers receiving 529 citations
Peiling Cai's Hit Papers
Peers
Comparison fields: 5 of 90
- Cancer Research 57
- Molecular Biology 261
- Microbiology 17
- Oncology 62
- Oral Surgery 14
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 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 98 | |
| 2 | Deep-STP: a deep learning-based approach to predict snake toxin proteins by using word embeddings Hit paper breakdown → | 2024 | 90 |
| 3 | 2023 | 47 | |
| 4 | 2017 | 38 | |
| 5 | 2021 | 24 | |
| 6 | 2024 | 24 | |
| 7 | 2016 | 23 | |
| 8 | 2017 | 22 | |
| 9 | 2022 | 18 | |
| 10 | 2025 | 17 | |
| 11 | 2016 | 17 | |
| 12 | 2015 | 13 | |
| 13 | 2024 | 12 | |
| 14 | 2023 | 11 | |
| 15 | 2018 | 11 | |
| 16 | 2017 | 10 | |
| 17 | 2018 | 9 | |
| 18 | 2017 | 6 | |
| 19 | 2024 | 5 | |
| 20 | 2022 | 5 |
About Peiling Cai
Peiling Cai is a scholar working on Molecular Biology, Oncology, Clinical Psychology, Cancer Research and Pulmonary and Respiratory Medicine, having authored 39 papers that have together received 540 indexed citations. Recurring topics across this work include Colorectal Cancer Treatments and Studies (4 papers), Cancer Genomics and Diagnostics (3 papers), Gut microbiota and health (3 papers), COVID-19 and Mental Health (3 papers), Impact of Technology on Adolescents (2 papers), Cancer Cells and Metastasis (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Caveolin-1 and cellular processes (2 papers). The work is most often cited by research in Cancer Research (57 citations), Molecular Biology (261 citations), Microbiology (17 citations), Oncology (62 citations) and Oral Surgery (14 citations). 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, Liping Ren, Xiaolong Yu, Hui Ding, Xiang Chen and Hasan Zulfiqar. Their work appears in journals such as Medicine, PLoS ONE, Frontiers in Public Health, Frontiers in Medicine and Frontiers in Endocrinology.
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.