Mao Ding
Impact in
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- MicroRNA in disease regulation
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- Computational Drug Discovery Methods
Papers in
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- Computational Drug Discovery Methods 8
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- Protein Structure and Dynamics 2
- Bioinformatics and Genomic Networks 2
- Co-authors
- Tao Song (6 shared papers)Shudong Wang (6 shared papers)Zhaohong Xie (4 shared papers)Jianzhong Bi (4 shared papers)Shunliang Xu (4 shared papers)Ping Wang (3 shared papers)Zhengyu Zhu (2 shared papers)Linlin Xu (3 shared papers)
In The Last Decade
Mao Ding
21 papers receiving 522 citations
Peers
Comparison fields: 5 of 93
- Cancer Research 113
- Computational Theory and Mathematics 106
- Neurology 45
- Developmental Neuroscience 19
- Molecular Biology 333
Countries citing papers authored by Mao Ding
This map shows the geographic impact of Mao Ding'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 Mao Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mao Ding more than expected).
Fields of papers citing papers by Mao Ding
This network shows the impact of papers produced by Mao Ding. 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 Mao Ding. The network helps show where Mao Ding may publish in the future.
Co-authors
The 25 scholars most cited alongside Mao Ding, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 230 | |
| 2 | 2022 | 54 | |
| 3 | 2021 | 44 | |
| 4 | 2021 | 43 | |
| 5 | 2020 | 33 | |
| 6 | 2020 | 20 | |
| 7 | 2022 | 17 | |
| 8 | 2020 | 12 | |
| 9 | 2020 | 11 | |
| 10 | 2021 | 11 | |
| 11 | 2021 | 10 | |
| 12 | 2023 | 9 | |
| 13 | 2020 | 8 | |
| 14 | 2020 | 6 | |
| 15 | 2021 | 5 | |
| 16 | 2023 | 4 | |
| 17 | 2025 | 3 | |
| 18 | 2021 | 1 | |
| 19 | 2024 | 1 | |
| 20 | 2021 | 1 |
About Mao Ding
Mao Ding is a scholar working on Computational Theory and Mathematics, Molecular Biology, Electrical and Electronic Engineering, Civil and Structural Engineering and Cognitive Neuroscience, having authored 21 papers that have together received 524 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (8 papers), Integrated Energy Systems Optimization (6 papers), Infrastructure Resilience and Vulnerability Analysis (3 papers), Geothermal Energy Systems and Applications (2 papers), Alzheimer's disease research and treatments (2 papers), Protein Structure and Dynamics (2 papers), Sleep and Wakefulness Research (2 papers) and Bioinformatics and Genomic Networks (2 papers). The work is most often cited by research in Cancer Research (113 citations), Computational Theory and Mathematics (106 citations), Neurology (45 citations), Developmental Neuroscience (19 citations) and Molecular Biology (333 citations). Mao Ding has collaborated with scholars based in China, Spain and France. Frequent co-authors include Tao Song, Shudong Wang, Zhaohong Xie, Jianzhong Bi, Shunliang Xu, Ping Wang, Zhengyu Zhu, Linlin Xu, Yang Shen and Alfonso Rodríguez‐Patón. Their work appears in journals such as Sustainable Cities and Society, Frontiers in Genetics, Applied Intelligence, Biomedical Materials and Molecular Informatics.
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.