Wang Jin
Impact in
- Modeling and Simulation top 2%
- Mathematical Biology Tumor Growth
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- Cellular Mechanics and Interactions
Papers in
-
- Mathematical Biology Tumor Growth 8
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- Gene Regulatory Network Analysis 7
- Single-cell and spatial transcriptomics 2
- Co-authors
- Matthew J. Simpson (14 shared papers)Scott W. McCue (9 shared papers)Catherine J. Penington (4 shared papers)Esha T. Shah (2 shared papers)Lisa K. Chopin (1 shared paper)Kai‐Yin Lo (3 shared papers)Yihong Du (1 shared paper)Timothy J. Moroney (1 shared paper)
- Journals
- Bulletin of Mathematical Biology (3 papers)Journal of Theoretical Biology (2 papers)Chemical Engineering Science (2 papers)Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences (1 paper)Computer Methods and Programs in Biomedicine (1 paper)
- Partner nations
- AustraliaTaiwanNew Zealand
In The Last Decade
Wang Jin
14 papers receiving 355 citations
Peers
Comparison fields: 5 of 90
- Modeling and Simulation 132
- Cell Biology 67
- Public Health, Environmental and Occupational Health 81
- Rehabilitation 15
- Genetics 64
Countries citing papers authored by Wang Jin
This map shows the geographic impact of Wang Jin'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 Wang Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wang Jin more than expected).
Fields of papers citing papers by Wang Jin
This network shows the impact of papers produced by Wang Jin. 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 Wang Jin. The network helps show where Wang Jin may publish in the future.
Co-authors
The 25 scholars most cited alongside Wang Jin, 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 | 2015 | 78 | |
| 2 | 2019 | 51 | |
| 3 | 2019 | 33 | |
| 4 | 2017 | 31 | |
| 5 | 2018 | 28 | |
| 6 | 2018 | 27 | |
| 7 | 2019 | 24 | |
| 8 | 2016 | 19 | |
| 9 | 2017 | 14 | |
| 10 | 2021 | 14 | |
| 11 | 2020 | 13 | |
| 12 | 2021 | 11 | |
| 13 | 2018 | 10 | |
| 14 | 2020 | 4 | |
| 15 | 2025 | 0 |
About Wang Jin
Wang Jin is a scholar working on Modeling and Simulation, Molecular Biology, Cell Biology, Genetics and Biomedical Engineering, having authored 15 papers that have together received 357 indexed citations. Recurring topics across this work include Mathematical Biology Tumor Growth (8 papers), Gene Regulatory Network Analysis (7 papers), Evolution and Genetic Dynamics (3 papers), Marine and fisheries research (2 papers), Mathematical and Theoretical Epidemiology and Ecology Models (2 papers), Single-cell and spatial transcriptomics (2 papers), Coral and Marine Ecosystems Studies (2 papers) and Cellular Mechanics and Interactions (2 papers). The work is most often cited by research in Modeling and Simulation (132 citations), Cell Biology (67 citations), Public Health, Environmental and Occupational Health (81 citations), Rehabilitation (15 citations) and Genetics (64 citations). Wang Jin has collaborated with scholars based in Australia, Taiwan and New Zealand. Frequent co-authors include Matthew J. Simpson, Scott W. McCue, Catherine J. Penington, Esha T. Shah, Lisa K. Chopin, Kai‐Yin Lo, Yihong Du, Timothy J. Moroney, Philip K. Maini and Nikolas K. Haass. Their work appears in journals such as Bulletin of Mathematical Biology, Journal of Theoretical Biology, Chemical Engineering Science, Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences and Computer Methods and Programs in Biomedicine.
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.