Guiying Yan
- Molecular Biology top 1%
- Cancer Research top 0.2%
- Computational Theory and Mathematics top 0.5%
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Topics
- Cancer-related molecular mechanisms research (21 papers)MicroRNA in disease regulation (15 papers)Bioinformatics and Genomic Networks (12 papers)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Guiying Yan
77 papers receiving 5.1k citations
Hit Papers
Peers
Comparison fields: 5 of 140
- Molecular Biology 4.2k
- Cancer Research 3.2k
- Computational Theory and Mathematics 748
- Artificial Intelligence 191
- Electrical and Electronic Engineering 187
Countries citing papers authored by Guiying Yan
This map shows the geographic impact of Guiying Yan'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 Guiying Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guiying Yan more than expected).
Fields of papers citing papers by Guiying Yan
This network shows the impact of papers produced by Guiying Yan. 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 Guiying Yan. The network helps show where Guiying Yan may publish in the future.
Co-authorship network of co-authors of Guiying Yan
This figure shows the co-authorship network connecting the top 25 collaborators of Guiying Yan. A scholar is included among the top collaborators of Guiying Yan 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 Guiying Yan. Guiying Yan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 10 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 5 | |
| 9 | 44 | |
| 10 | 325 | |
| 11 | 106 | |
| 12 | 9 | |
| 13 | 236 | |
| 14 | 2 | |
| 15 | 110 | |
| 16 | 325 | |
| 17 | Drug–target interaction prediction by random walk on the heterogeneous networkbreakdown → | 417 |
| 18 | 366 | |
| 19 | LncRNADisease: a database for long-non-coding RNA-associated diseasesbreakdown → | 748 |
| 20 | Linear vertex arboricity, independence number and clique cover number | 1 |
About Guiying Yan
Guiying Yan is a scholar working on Discrete Mathematics and Combinatorics, Cancer Research and Computational Theory and Mathematics, having authored 83 papers that have together received 5.1k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (21 papers), MicroRNA in disease regulation (15 papers) and Bioinformatics and Genomic Networks (12 papers). The work is most often cited by research in Cancer Research (3.2k citations), Molecular Biology (4.2k citations) and Computational Theory and Mathematics (748 citations). Guiying Yan has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Xing Chen, Xing Chen, Ming-Xi Liu, Zhu‐Hong You, Qinghua Cui, Geng Chen, Yu‐An Huang, Zhi-An Huang, Mingxi Liu and Qipeng Zhang. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and PLoS ONE.
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.