Shaoyong Lu
Impact in
- Computational Theory and Mathematics top 0.2%
- Computational Drug Discovery Methods
- Molecular Biology top 1%
- Protein Structure and Dynamics
- Receptor Mechanisms and Signaling
- Protein Kinase Regulation and GTPase Signaling
- PI3K/AKT/mTOR signaling in cancer
- RNA and protein synthesis mechanisms
- Chemical Synthesis and Analysis
Papers in
-
- Computational Drug Discovery Methods 36
-
- Receptor Mechanisms and Signaling 38
- Protein Structure and Dynamics 31
- Protein Kinase Regulation and GTPase Signaling 29
- PI3K/AKT/mTOR signaling in cancer 16
- Chemical Synthesis and Analysis 12
- Journals
- Drug Discovery Today (9 papers)Nucleic Acids Research (6 papers)Journal of Chemical Information and Modeling (6 papers)Computational and Structural Biotechnology Journal (5 papers)International Journal of Biological Macromolecules (5 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Shaoyong Lu
140 papers receiving 5.6k citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Computational Theory and Mathematics 1.4k
- Molecular Biology 4.7k
- Toxicology 103
- Cellular and Molecular Neuroscience 408
- Physiology 101
Countries citing papers authored by Shaoyong Lu
This map shows the geographic impact of Shaoyong Lu'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 Shaoyong Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaoyong Lu more than expected).
Fields of papers citing papers by Shaoyong Lu
This network shows the impact of papers produced by Shaoyong Lu. 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 Shaoyong Lu. The network helps show where Shaoyong Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Shaoyong Lu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 6 | |
| 2 | 2025 | 4 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 3 | |
| 5 | 2024 | 14 | |
| 6 | 2023 | 3 | |
| 7 | 2022 | 10 | |
| 8 | 2021 | 33 | |
| 9 | 2021 | 160 | |
| 10 | 2021 | 52 | |
| 11 | 2021 | 29 | |
| 12 | 2020 | 49 | |
| 13 | 2020 | 108 | |
| 14 | 2019 | 55 | |
| 15 | 2019 | 34 | |
| 16 | 2019 | 137 | |
| 17 | 2018 | 10 | |
| 18 | 2018 | 78 | |
| 19 | 2018 | 20 | |
| 20 | 2017 | 98 |
About Shaoyong Lu
Shaoyong Lu is a scholar working on Computational Theory and Mathematics, Molecular Biology, Geriatrics and Gerontology, Physiology and Toxicology, having authored 143 papers that have together received 5.7k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (38 papers), Computational Drug Discovery Methods (36 papers), Protein Structure and Dynamics (31 papers), Protein Kinase Regulation and GTPase Signaling (29 papers), PI3K/AKT/mTOR signaling in cancer (16 papers), Neuropeptides and Animal Physiology (14 papers), Enzyme Structure and Function (12 papers) and Chemical Synthesis and Analysis (12 papers). The work is most often cited by research in Computational Theory and Mathematics (1.4k citations), Molecular Biology (4.7k citations), Toxicology (103 citations), Cellular and Molecular Neuroscience (408 citations) and Physiology (101 citations). Shaoyong Lu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Jian Zhang, Duan Ni, Ruth Nussinov, Hyunbum Jang, Qiancheng Shen, Xinheng He, Wenkang Huang, Jun Pu, Yuran Qiu and Shuai Li. Their work appears in journals such as Drug Discovery Today, Nucleic Acids Research, Journal of Chemical Information and Modeling, Computational and Structural Biotechnology Journal and International Journal of Biological Macromolecules.
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.