Junbo Gao
Impact in
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- Computational Drug Discovery Methods
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- Protein Degradation and Inhibitors
- Protein Structure and Dynamics
- Ubiquitin and proteasome pathways
- Natural product bioactivities and synthesis
Papers in
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- Natural product bioactivities and synthesis 7
- Biological Activity of Diterpenoids and Biflavonoids 4
- Protein Structure and Dynamics 4
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- Computational Drug Discovery Methods 9
- Co-authors
- Tingjun Hou (9 shared papers)Dongsheng Cao (7 shared papers)Gaoqi Weng (3 shared papers)Zhe Wang (4 shared papers)Dan Li (4 shared papers)Xueping Hu (3 shared papers)Yu Kang (5 shared papers)Chao Shen (4 shared papers)
In The Last Decade
Junbo Gao
45 papers receiving 978 citations
Peers
Comparison fields: 5 of 107
- Computational Theory and Mathematics 299
- Molecular Biology 624
- Pharmacology 94
- Oncology 113
- Pharmacology 38
Countries citing papers authored by Junbo Gao
This map shows the geographic impact of Junbo Gao'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 Junbo Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junbo Gao more than expected).
Fields of papers citing papers by Junbo Gao
This network shows the impact of papers produced by Junbo Gao. 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 Junbo Gao. The network helps show where Junbo Gao may publish in the future.
Co-authors
The 25 scholars most cited alongside Junbo Gao, 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 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 150 | |
| 2 | 2020 | 122 | |
| 3 | 2022 | 121 | |
| 4 | 2020 | 85 | |
| 5 | 2020 | 55 | |
| 6 | 2022 | 45 | |
| 7 | 2020 | 32 | |
| 8 | 2021 | 27 | |
| 9 | 2018 | 25 | |
| 10 | 2017 | 24 | |
| 11 | 2019 | 24 | |
| 12 | 2019 | 20 | |
| 13 | 2022 | 19 | |
| 14 | 2018 | 18 | |
| 15 | 2022 | 18 | |
| 16 | 2018 | 17 | |
| 17 | 2023 | 16 | |
| 18 | 2019 | 15 | |
| 19 | 2020 | 14 | |
| 20 | 2018 | 14 |
About Junbo Gao
Junbo Gao is a scholar working on Molecular Biology, Computational Theory and Mathematics, Plant Science, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 48 papers that have together received 986 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (9 papers), Phytochemistry and Biological Activities (8 papers), Natural product bioactivities and synthesis (7 papers), Biological Activity of Diterpenoids and Biflavonoids (4 papers), Traffic Prediction and Management Techniques (4 papers), Protein Structure and Dynamics (4 papers), Colorectal Cancer Screening and Detection (4 papers) and Traffic control and management (3 papers). The work is most often cited by research in Computational Theory and Mathematics (299 citations), Molecular Biology (624 citations), Pharmacology (94 citations), Oncology (113 citations) and Pharmacology (38 citations). Junbo Gao has collaborated with scholars based in China, Macao and Malaysia. Frequent co-authors include Tingjun Hou, Dongsheng Cao, Gaoqi Weng, Zhe Wang, Dan Li, Xueping Hu, Yu Kang, Chao Shen, Wei‐Lie Xiao and Xujun Zhang. Their work appears in journals such as Journal of Natural Products, Nucleic Acids Research, Biomedical Signal Processing and Control, Applied Intelligence and Emerging Microbes & Infections.
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.