Xiaofeng Song
Impact in
- Cancer Research top 1%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Molecular Biology top 5%
- Circular RNAs in diseases
- RNA modifications and cancer
- RNA Research and Splicing
- Genomics and Phylogenetic Studies
- RNA and protein synthesis mechanisms
Papers in
-
- MicroRNA in disease regulation 17
- Cancer-related molecular mechanisms research 16
-
- Circular RNAs in diseases 15
- RNA modifications and cancer 14
- RNA and protein synthesis mechanisms 11
- RNA Research and Splicing 9
- Machine Learning in Bioinformatics 5
- Co-authors
- Ping HanXuejiang GuoYan LiTao ZhouXiaoping ChenTianyi XuJing WuZhongming Zhao
- Journals
- Scientific Reports (4 papers)Computers in Biology and Medicine (4 papers)PLoS ONE (4 papers)Nucleic Acids Research (3 papers)BMC Genomics (3 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Xiaofeng Song
78 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 134
- Cancer Research 1.2k
- Molecular Biology 1.9k
- Plant Science 345
- Endocrinology 36
- Cell Biology 106
Countries citing papers authored by Xiaofeng Song
This map shows the geographic impact of Xiaofeng Song'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 Xiaofeng Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaofeng Song more than expected).
Fields of papers citing papers by Xiaofeng Song
This network shows the impact of papers produced by Xiaofeng Song. 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 Xiaofeng Song. The network helps show where Xiaofeng Song may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaofeng Song, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 7 | |
| 5 | 2023 | 3 | |
| 6 | 2022 | 16 | |
| 7 | 2022 | 3 | |
| 8 | 2021 | 5 | |
| 9 | 2020 | 8 | |
| 10 | 2020 | 19 | |
| 11 | 2019 | 43 | |
| 12 | 2017 | 198 | |
| 13 | 2016 | 17 | |
| 14 | 2014 | 1 | |
| 15 | 2013 | 134 | |
| 16 | 2012 | 29 | |
| 17 | 2011 | 8 | |
| 18 | 2010 | 9 | |
| 19 | 2008 | 51 | |
| 20 | [A review on the eco-physiological study of poplars in oasis and its prospect]. | 2000 | 4 |
About Xiaofeng Song
Xiaofeng Song is a scholar working on Cancer Research, Molecular Biology, Aging, Management Information Systems and Biochemistry, having authored 86 papers that have together received 2.5k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (17 papers), Cancer-related molecular mechanisms research (16 papers), Circular RNAs in diseases (15 papers), RNA modifications and cancer (14 papers), RNA and protein synthesis mechanisms (11 papers), RNA Research and Splicing (9 papers), Machine Learning in Bioinformatics (5 papers) and Viral Infections and Immunology Research (4 papers). The work is most often cited by research in Cancer Research (1.2k citations), Molecular Biology (1.9k citations), Plant Science (345 citations), Endocrinology (36 citations) and Cell Biology (106 citations). Xiaofeng Song has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Ping Han, Xuejiang Guo, Yan Li, Tao Zhou, Xiaoping Chen, Tianyi Xu, Jing Wu, Zhongming Zhao, Kai Wang and Ben Fan. Their work appears in journals such as Scientific Reports, Computers in Biology and Medicine, PLoS ONE, Nucleic Acids Research and BMC Genomics.
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.