Keming Song
- Plant Science top 0.5%
- Molecular Biology top 2%
- Genetics top 2%
- Ecology, Evolution, Behavior and Systematics top 2%
- Cell Biology top 10%
- Co-authors
- T. C. OsbornKathy F.J. TangCraig S. PikaardOlga PontesKeith EarleyJeremy R. HaagPeng LüPaul H. Williams
- Topics
- Plant Disease Resistance and Genetics (8 papers)Chromosomal and Genetic Variations (6 papers)Genomics and Phylogenetic Studies (5 papers)
- Journals
- Proceedings of the National Academy of SciencesThe Plant JournalTheoretical and Applied Genetics
- Partner nations
- United StatesPortugal
In The Last Decade
Keming Song
16 papers receiving 3.9k citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Plant Science 3.2k
- Molecular Biology 2.7k
- Genetics 715
- Ecology, Evolution, Behavior and Systematics 439
- Cell Biology 142
Countries citing papers authored by Keming Song
This map shows the geographic impact of Keming 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 Keming Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keming Song more than expected).
Fields of papers citing papers by Keming Song
This network shows the impact of papers produced by Keming 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 Keming Song. The network helps show where Keming Song may publish in the future.
Co-authorship network of co-authors of Keming Song
This figure shows the co-authorship network connecting the top 25 collaborators of Keming Song. A scholar is included among the top collaborators of Keming Song based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Keming Song. Keming Song is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Gateway‐compatible vectors for plant functional genomics and proteomicsbreakdown → | 1463 |
| 2 | 136 | |
| 3 | 271 | |
| 4 | 113 | |
| 5 | 2 | |
| 6 | 54 | |
| 7 | Rapid genome change in synthetic polyploids of Brassica and its implications for polyploid evolution.breakdown → | 818 |
| 8 | 13 | |
| 9 | 73 | |
| 10 | 110 | |
| 11 | 155 | |
| 12 | 16 | |
| 13 | 188 | |
| 14 | 258 | |
| 15 | 366 | |
| 16 | 87 |
About Keming Song
Keming Song is a scholar working on Plant Science, Molecular Biology and Biotechnology, having authored 16 papers that have together received 4.1k indexed citations. Recurring topics across this work include Plant Disease Resistance and Genetics (8 papers), Chromosomal and Genetic Variations (6 papers) and Genomics and Phylogenetic Studies (5 papers). The work is most often cited by research in Plant Science (3.2k citations), Molecular Biology (2.7k citations) and Horticulture (33 citations). Keming Song has collaborated with scholars based in United States and Portugal. Frequent co-authors include T. C. Osborn, T. C. Osborn, Kathy F.J. Tang, Craig S. Pikaard, Olga Pontes, Keith Earley, Jeremy R. Haag, Peng Lü, Paul H. Williams and P. H. Williams. Their work appears in journals such as Proceedings of the National Academy of Sciences, The Plant Journal and Theoretical and Applied Genetics.
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.