Shaohua Shi
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- Computational Drug Discovery Methods 10
- Pharmacology top 10%
- Pharmacogenetics and Drug Metabolism 2
- Pharmacological Effects of Natural Compounds 2
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- Synthesis and biological activity 1
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- Pharmacogenetics and Drug Metabolism 2
- Pharmacological Effects of Natural Compounds 2
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- Machine Learning in Materials Science 4
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- Metabolomics and Mass Spectrometry Studies 2
- Protein Structure and Dynamics 1
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- Energy, Environment, Economic Growth 1
Shaohua Shi
14 papers receiving 577 citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Computational Theory and Mathematics 208
- Pharmacology 79
- Complementary and alternative medicine 44
- Organic Chemistry 117
- Pharmacology 64
Countries citing papers authored by Shaohua Shi
This map shows the geographic impact of Shaohua Shi'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 Shaohua Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaohua Shi more than expected).
Fields of papers citing papers by Shaohua Shi
This network shows the impact of papers produced by Shaohua Shi. 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 Shaohua Shi. The network helps show where Shaohua Shi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shaohua Shi, 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 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 13 | |
| 5 | 2024 | 23 | |
| 6 | ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision supportbreakdown → | 2024 | 349 |
| 7 | 2024 | 9 | |
| 8 | 2024 | 7 | |
| 9 | 2023 | 10 | |
| 10 | 2023 | 18 | |
| 11 | 2022 | 25 | |
| 12 | 2022 | 24 | |
| 13 | 2021 | 3 | |
| 14 | 2014 | 80 | |
| 15 | 2013 | 30 | |
| 16 | 2013 | 2 |
About Shaohua Shi
Shaohua Shi is a scholar working on Computational Theory and Mathematics, Pharmacology, Molecular Medicine, Hepatology and Pharmacology, having authored 16 papers that have together received 594 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (10 papers), Machine Learning in Materials Science (4 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Pharmacogenetics and Drug Metabolism (2 papers), Pharmacological Effects of Natural Compounds (2 papers), Energy, Environment, Economic Growth (1 paper), Protein Structure and Dynamics (1 paper) and Synthesis and biological activity (1 paper). The work is most often cited by research in Computational Theory and Mathematics (208 citations), Pharmacology (79 citations), Complementary and alternative medicine (44 citations), Organic Chemistry (117 citations) and Pharmacology (64 citations). Shaohua Shi has collaborated with scholars based in China, Hong Kong and Chile. Frequent co-authors include Dongsheng Cao, Tingjun Hou, Xiangxiang Zeng, Chengkun Wu, Jiacai Yi, Youchao Deng, Zhenhua Wu, Jinfu Peng, Wenxuan Wang and Aiping Lyu. Their work appears in journals such as Journal of Chemical Information and Modeling, Nucleic Acids Research, Engineering With Computers, Analytical Methods and Drug Discovery Today.
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.