Lu-Yun Lian
- Molecular Biology top 10%
- Cell Biology top 10%
- Pharmacology top 2%
- Public Health, Environmental and Occupational Health top 10%
- Genetics
- Co-authors
- Alexander P. GolovanovStuart A. WilsonGuillaume M. HautbergueGordon C. K. RobertsIgor BarsukovMichael J. SutcliffeSandeep ModiJeremy P. Derrick
- Topics
- Protein Structure and Dynamics (6 papers)RNA and protein synthesis mechanisms (4 papers)Enzyme Structure and Function (4 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Chemical SocietyJournal of Molecular Biology
- Partner nations
- United KingdomUnited StatesNorway
In The Last Decade
Lu-Yun Lian
25 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 99
- Molecular Biology 1.2k
- Cell Biology 173
- Pharmacology 166
- Public Health, Environmental and Occupational Health 157
- Genetics 155
Countries citing papers authored by Lu-Yun Lian
This map shows the geographic impact of Lu-Yun Lian'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 Lu-Yun Lian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lu-Yun Lian more than expected).
Fields of papers citing papers by Lu-Yun Lian
This network shows the impact of papers produced by Lu-Yun Lian. 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 Lu-Yun Lian. The network helps show where Lu-Yun Lian may publish in the future.
Co-authorship network of co-authors of Lu-Yun Lian
This figure shows the co-authorship network connecting the top 25 collaborators of Lu-Yun Lian. A scholar is included among the top collaborators of Lu-Yun Lian 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 Lu-Yun Lian. Lu-Yun Lian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 26 | |
| 2 | 65 | |
| 3 | 59 | |
| 4 | 204 | |
| 5 | 148 | |
| 6 | 42 | |
| 7 | 33 | |
| 8 | 10 | |
| 9 | 367 | |
| 10 | 19 | |
| 11 | 41 | |
| 12 | 53 | |
| 13 | 37 | |
| 14 | 20 | |
| 15 | 34 | |
| 16 | 22 | |
| 17 | 28 | |
| 18 | 94 | |
| 19 | 52 | |
| 20 | 76 |
About Lu-Yun Lian
Lu-Yun Lian is a scholar working on Microbiology, Molecular Biology and Nuclear and High Energy Physics, having authored 25 papers that have together received 1.6k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (6 papers), RNA and protein synthesis mechanisms (4 papers) and Enzyme Structure and Function (4 papers). The work is most often cited by research in Pharmacology (166 citations), Molecular Biology (1.2k citations) and Cell Biology (173 citations). Lu-Yun Lian has collaborated with scholars based in United Kingdom, United States and Norway. Frequent co-authors include Alexander P. Golovanov, Stuart A. Wilson, Guillaume M. Hautbergue, Gordon C. K. Roberts, Igor Barsukov, Michael J. Sutcliffe, Sandeep Modi, Jeremy P. Derrick, Mark J. I. Paine and William U. Primrose. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Molecular Biology.
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.