Shikui Tu
Impact in
- Aging top 1%
- Genetics, Aging, and Longevity in Model Organisms
- Molecular Biology top 10%
- CRISPR and Genetic Engineering
- RNA Research and Splicing
- RNA modifications and cancer
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
Papers in
-
- CRISPR and Genetic Engineering 13
- Bioinformatics and Genomic Networks 10
- Gene expression and cancer classification 9
- Protein Structure and Dynamics 6
- Co-authors
- Zhiping Weng (14 shared papers)Lei Xu (42 shared papers)Heng-Chi Lee (6 shared papers)Craig C. Mello (4 shared papers)Wen Tang (4 shared papers)Wen Zhang (4 shared papers)Wei-Sheng Wu (4 shared papers)Swapnil S. Parhad (3 shared papers)
- Journals
- Nucleic Acids Research (4 papers)Neural Networks (4 papers)Cell (3 papers)Cell Reports (2 papers)IEEE Access (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Shikui Tu
78 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 115
- Aging 205
- Molecular Biology 1.2k
- Plant Science 565
- Computational Theory and Mathematics 229
- Cancer Research 145
Countries citing papers authored by Shikui Tu
This map shows the geographic impact of Shikui Tu'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 Shikui Tu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shikui Tu more than expected).
Fields of papers citing papers by Shikui Tu
This network shows the impact of papers produced by Shikui Tu. 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 Shikui Tu. The network helps show where Shikui Tu may publish in the future.
Co-authors
The 25 scholars most cited alongside Shikui Tu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 172 | |
| 2 | 2014 | 169 | |
| 3 | 2018 | 161 | |
| 4 | 2016 | 105 | |
| 5 | 2019 | 64 | |
| 6 | 2016 | 63 | |
| 7 | 2021 | 62 | |
| 8 | 2016 | 59 | |
| 9 | 2017 | 58 | |
| 10 | 2017 | 54 | |
| 11 | 2018 | 48 | |
| 12 | 2020 | 43 | |
| 13 | 2018 | 36 | |
| 14 | 2018 | 34 | |
| 15 | 2018 | 34 | |
| 16 | 2022 | 33 | |
| 17 | 2023 | 32 | |
| 18 | 2014 | 32 | |
| 19 | 2019 | 28 | |
| 20 | 2018 | 23 |
About Shikui Tu
Shikui Tu is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Artificial Intelligence and Plant Science, having authored 87 papers that have together received 1.7k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (15 papers), CRISPR and Genetic Engineering (13 papers), Chromosomal and Genetic Variations (13 papers), Bioinformatics and Genomic Networks (10 papers), Genetics, Aging, and Longevity in Model Organisms (9 papers), Gene expression and cancer classification (9 papers), Protein Structure and Dynamics (6 papers) and EEG and Brain-Computer Interfaces (5 papers). The work is most often cited by research in Aging (205 citations), Molecular Biology (1.2k citations), Plant Science (565 citations), Computational Theory and Mathematics (229 citations) and Cancer Research (145 citations). Shikui Tu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Zhiping Weng, Lei Xu, Heng-Chi Lee, Craig C. Mello, Wen Tang, Wen Zhang, Wei-Sheng Wu, Swapnil S. Parhad, William E. Theurkauf and Donglei Zhang. Their work appears in journals such as Nucleic Acids Research, Neural Networks, Cell, Cell Reports and IEEE Access.
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.