Yihui Liu
- Molecular Biology
- Genetics
- Artificial Intelligence
- Computational Theory and Mathematics top 5%
- Ecology, Evolution, Behavior and Systematics top 10%
- Co-authors
- Jinyong ChengHitoshi SakioChen ChenShota SakaguchiYingxiong QiuXinshuai QiHans Peter ComesNobuyuki Tanaka
- Topics
- Machine Learning in Bioinformatics (28 papers)Protein Structure and Dynamics (16 papers)Gene expression and cancer classification (12 papers)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Yihui Liu
71 papers receiving 803 citations
Peers
Comparison fields: 5 of 131
- Molecular Biology 451
- Genetics 101
- Artificial Intelligence 91
- Computational Theory and Mathematics 91
- Ecology, Evolution, Behavior and Systematics 75
Countries citing papers authored by Yihui Liu
This map shows the geographic impact of Yihui Liu'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 Yihui Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yihui Liu more than expected).
Fields of papers citing papers by Yihui Liu
This network shows the impact of papers produced by Yihui Liu. 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 Yihui Liu. The network helps show where Yihui Liu may publish in the future.
Co-authorship network of co-authors of Yihui Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Yihui Liu. A scholar is included among the top collaborators of Yihui Liu 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 Yihui Liu. Yihui Liu 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 | 5 | |
| 3 | 10 | |
| 4 | 6 | |
| 5 | 12 | |
| 6 | 14 | |
| 7 | 16 | |
| 8 | 6 | |
| 9 | 37 | |
| 10 | 6 | |
| 11 | 12 | |
| 12 | 12 | |
| 13 | 1 | |
| 14 | Classificatioo of MR Tumor Images Based on Gabor Wavelet Analysis | 31 |
| 15 | 148 | |
| 16 | Wavelet high-frequency coefficients for feature extraction of gene microarray data | 1 |
| 17 | Classification of 31P MRS Data for Liver Cancer. | 1 |
| 18 | Wavelet Vector Flow: A New External Force of Snakes for Medical Image Analysis. | 1 |
| 19 | Neural Networks and Wavelets for Face Recognition. | 1 |
| 20 | 51 |
About Yihui Liu
Yihui Liu is a scholar working on Analytical Chemistry, Biophysics and Computational Theory and Mathematics, having authored 74 papers that have together received 837 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (28 papers), Protein Structure and Dynamics (16 papers) and Gene expression and cancer classification (12 papers). The work is most often cited by research in Ecological Modeling (31 citations), Molecular Biology (451 citations) and Computational Theory and Mathematics (91 citations). Yihui Liu has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Jinyong Cheng, Hitoshi Sakio, Chen Chen, Shota Sakaguchi, Yingxiong Qiu, Xinshuai Qi, Hans Peter Comes, Nobuyuki Tanaka, Ruixiang Li and Stephan Ladisch. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry 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.