Jin Xie
Impact in
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- Urinary Bladder and Prostate Research
Papers in
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- Metaheuristic Optimization Algorithms Research 5
- Evolutionary Algorithms and Applications 4
- Machine Learning and ELM 2
- Co-authors
- Sabatino Ventura (3 shared papers)Carl W. White (1 shared paper)Weifeng Gao (6 shared papers)Hong Li (5 shared papers)Colin W. Pouton (2 shared papers)Ben Capuano (1 shared paper)Aaron DeBono (1 shared paper)Peter J. Scammells (1 shared paper)
- Journals
- Information Sciences (2 papers)Habitat International (2 papers)Nature Communications (1 paper)Chinese Chemical Letters (1 paper)Cell Discovery (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Jin Xie
22 papers receiving 268 citations
Peers
Comparison fields: 5 of 98
- Urology 14
- Urban Studies 12
- Organic Chemistry 52
- Computational Theory and Mathematics 26
- Toxicology 5
Countries citing papers authored by Jin Xie
This map shows the geographic impact of Jin Xie'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 Jin Xie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jin Xie more than expected).
Fields of papers citing papers by Jin Xie
This network shows the impact of papers produced by Jin Xie. 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 Jin Xie. The network helps show where Jin Xie may publish in the future.
Co-authors
The 25 scholars most cited alongside Jin Xie, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 44 | |
| 2 | 2013 | 43 | |
| 3 | 2001 | 28 | |
| 4 | 2016 | 22 | |
| 5 | 2023 | 17 | |
| 6 | 2020 | 16 | |
| 7 | 2022 | 14 | |
| 8 | 2018 | 12 | |
| 9 | 2010 | 11 | |
| 10 | 2017 | 10 | |
| 11 | 2024 | 9 | |
| 12 | 2018 | 8 | |
| 13 | 2025 | 7 | |
| 14 | 2022 | 7 | |
| 15 | 2020 | 7 | |
| 16 | 2024 | 5 | |
| 17 | 2022 | 3 | |
| 18 | 2009 | 2 | |
| 19 | 2023 | 2 | |
| 20 | 2022 | 2 |
About Jin Xie
Jin Xie is a scholar working on Molecular Biology, Artificial Intelligence, Computational Theory and Mathematics, Organic Chemistry and Pharmacology, having authored 23 papers that have together received 271 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (5 papers), Evolutionary Algorithms and Applications (4 papers), Advanced Multi-Objective Optimization Algorithms (4 papers), Computational Drug Discovery Methods (2 papers), Free Radicals and Antioxidants (2 papers), Housing Market and Economics (2 papers), Urban and Rural Development Challenges (2 papers) and Machine Learning and ELM (2 papers). The work is most often cited by research in Urology (14 citations), Urban Studies (12 citations), Organic Chemistry (52 citations), Computational Theory and Mathematics (26 citations) and Toxicology (5 citations). Jin Xie has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Sabatino Ventura, Carl W. White, Weifeng Gao, Hong Li, Colin W. Pouton, Ben Capuano, Aaron DeBono, Peter J. Scammells, Richard A. Mathies and Lorenzo Berti. Their work appears in journals such as Information Sciences, Habitat International, Nature Communications, Chinese Chemical Letters and Cell Discovery.
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.