Haifeng Wan
Impact in
- Reproductive Medicine top 2%
- Sperm and Testicular Function
- Aging top 5%
Papers in
-
- Pluripotent Stem Cells Research 22
- CRISPR and Genetic Engineering 16
- Renal and related cancers 9
- Single-cell and spatial transcriptomics 4
- Genetics 8
- Animal Genetics and Reproduction 7
- Co-authors
- Qi Zhou (25 shared papers)Xiaoyang Zhao (16 shared papers)Guihai Feng (12 shared papers)Yan Yuan (5 shared papers)Jiahao Sha (3 shared papers)Quan Zhou (4 shared papers)Xuepeng Wang (5 shared papers)Rui Fu (5 shared papers)
- Journals
- Cell stem cell (4 papers)Cell Research (3 papers)Nature (3 papers)Scientific Reports (2 papers)Cell Proliferation (1 paper)
- Partner nations
- ChinaUnited StatesIndia
In The Last Decade
Haifeng Wan
32 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 98
- Reproductive Medicine 233
- Aging 40
- Geriatrics and Gerontology 59
- Molecular Biology 1.2k
- Public Health, Environmental and Occupational Health 362
Countries citing papers authored by Haifeng Wan
This map shows the geographic impact of Haifeng Wan'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 Haifeng Wan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haifeng Wan more than expected).
Fields of papers citing papers by Haifeng Wan
This network shows the impact of papers produced by Haifeng Wan. 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 Haifeng Wan. The network helps show where Haifeng Wan may publish in the future.
Co-authors
The 25 scholars most cited alongside Haifeng Wan, 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 303 | |
| 2 | 2014 | 216 | |
| 3 | 2019 | 146 | |
| 4 | 2012 | 134 | |
| 5 | 2018 | 129 | |
| 6 | 2011 | 116 | |
| 7 | 2020 | 98 | |
| 8 | 2013 | 80 | |
| 9 | 2022 | 54 | |
| 10 | 2018 | 53 | |
| 11 | 2020 | 51 | |
| 12 | 2016 | 40 | |
| 13 | 2019 | 33 | |
| 14 | 2017 | 27 | |
| 15 | 2015 | 20 | |
| 16 | 2016 | 19 | |
| 17 | 2015 | 18 | |
| 18 | 2015 | 18 | |
| 19 | 2017 | 17 | |
| 20 | 2016 | 14 |
About Haifeng Wan
Haifeng Wan is a scholar working on Molecular Biology, Genetics, Public Health, Environmental and Occupational Health, Cancer Research and Immunology, having authored 32 papers that have together received 1.7k indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (22 papers), CRISPR and Genetic Engineering (16 papers), Renal and related cancers (9 papers), Animal Genetics and Reproduction (7 papers), Reproductive Biology and Fertility (5 papers), Single-cell and spatial transcriptomics (4 papers), MicroRNA in disease regulation (3 papers) and Reproductive System and Pregnancy (2 papers). The work is most often cited by research in Reproductive Medicine (233 citations), Aging (40 citations), Geriatrics and Gerontology (59 citations), Molecular Biology (1.2k citations) and Public Health, Environmental and Occupational Health (362 citations). Haifeng Wan has collaborated with scholars based in China, United States and India. Frequent co-authors include Qi Zhou, Xiaoyang Zhao, Guihai Feng, Yan Yuan, Jiahao Sha, Quan Zhou, Xuepeng Wang, Rui Fu, Mei Wang and Wei Li. Their work appears in journals such as Cell stem cell, Cell Research, Nature, Scientific Reports and Cell Proliferation.
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.