Guifeng Wei
Impact in
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- Aging top 10%
Papers in
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- RNA modifications and cancer 17
- RNA Research and Splicing 16
- Genomics and Chromatin Dynamics 6
- CRISPR and Genetic Engineering 5
- Ubiquitin and proteasome pathways 2
-
- Cancer-related molecular mechanisms research 11
- Co-authors
- Neil Brockdorff (11 shared papers)Heather Coker (6 shared papers)Joseph S. Bowness (5 shared papers)Tatyana B. Nesterova (6 shared papers)Greta Pintacuda (3 shared papers)Runsheng Chen (12 shared papers)Benoît Moindrot (2 shared papers)Jianjun Luo (7 shared papers)
- Journals
- Nature Communications (2 papers)BMC Genomics (2 papers)Genes & Development (2 papers)Oncotarget (2 papers)Scientific Reports (2 papers)
- Partner nations
- United KingdomChinaUnited States
In The Last Decade
Guifeng Wei
31 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 92
- Cancer Research 555
- Aging 31
- Molecular Biology 1.1k
- Genetics 193
- Immunology 70
Countries citing papers authored by Guifeng Wei
This map shows the geographic impact of Guifeng Wei'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 Guifeng Wei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guifeng Wei more than expected).
Fields of papers citing papers by Guifeng Wei
This network shows the impact of papers produced by Guifeng Wei. 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 Guifeng Wei. The network helps show where Guifeng Wei may publish in the future.
Co-authors
The 25 scholars most cited alongside Guifeng Wei, 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 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 232 | |
| 2 | 2018 | 126 | |
| 3 | 2020 | 109 | |
| 4 | 2019 | 101 | |
| 5 | 2019 | 77 | |
| 6 | 2017 | 73 | |
| 7 | 2022 | 73 | |
| 8 | 2016 | 57 | |
| 9 | 2021 | 54 | |
| 10 | 2021 | 53 | |
| 11 | 2018 | 43 | |
| 12 | 2015 | 35 | |
| 13 | 2024 | 32 | |
| 14 | 2015 | 27 | |
| 15 | 2024 | 26 | |
| 16 | 2019 | 25 | |
| 17 | 2020 | 24 | |
| 18 | 2022 | 19 | |
| 19 | 2016 | 16 | |
| 20 | 2016 | 15 |
About Guifeng Wei
Guifeng Wei is a scholar working on Molecular Biology, Cancer Research, Genetics, Aging and Cellular and Molecular Neuroscience, having authored 33 papers that have together received 1.3k indexed citations. Recurring topics across this work include RNA modifications and cancer (17 papers), RNA Research and Splicing (16 papers), Cancer-related molecular mechanisms research (11 papers), Genomics and Chromatin Dynamics (6 papers), CRISPR and Genetic Engineering (5 papers), Genetics, Aging, and Longevity in Model Organisms (3 papers), Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities (3 papers) and Ubiquitin and proteasome pathways (2 papers). The work is most often cited by research in Cancer Research (555 citations), Aging (31 citations), Molecular Biology (1.1k citations), Genetics (193 citations) and Immunology (70 citations). Guifeng Wei has collaborated with scholars based in United Kingdom, China and United States. Frequent co-authors include Neil Brockdorff, Heather Coker, Joseph S. Bowness, Tatyana B. Nesterova, Greta Pintacuda, Runsheng Chen, Benoît Moindrot, Jianjun Luo, Alfredo Castelló and Shabaz Mohammed. Their work appears in journals such as Nature Communications, BMC Genomics, Genes & Development, Oncotarget and Scientific Reports.
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.