Ju Xiang
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
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- Cancer-related molecular mechanisms research
Papers in
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- Bioinformatics and Genomic Networks 34
- Machine Learning in Bioinformatics 16
- Gene expression and cancer classification 14
- Circular RNAs in diseases 7
- Gene Regulatory Network Analysis 7
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- Complex Network Analysis Techniques 22
- Opinion Dynamics and Social Influence 14
- Co-authors
- Liang Tang (26 shared papers)Jianming Li (25 shared papers)Min Li (17 shared papers)Ke Hu (13 shared papers)Meihua Bao (14 shared papers)Yiuman Tse (2 shared papers)Xiang Qin (12 shared papers)Fang‐Xiang Wu (10 shared papers)
- Journals
- Physica A Statistical Mechanics and its Applications (6 papers)IEEE/ACM Transactions on Computational Biology and Bioinformatics (5 papers)Frontiers in Genetics (5 papers)Briefings in Bioinformatics (4 papers)IEEE Access (3 papers)
- Partner nations
- ChinaCanadaUnited States
In The Last Decade
Ju Xiang
86 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 147
- Statistical and Nonlinear Physics 198
- Cancer Research 152
- Computational Theory and Mathematics 151
- Finance 84
- Molecular Biology 543
Countries citing papers authored by Ju Xiang
This map shows the geographic impact of Ju Xiang'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 Ju Xiang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ju Xiang more than expected).
Fields of papers citing papers by Ju Xiang
This network shows the impact of papers produced by Ju Xiang. 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 Ju Xiang. The network helps show where Ju Xiang may publish in the future.
Co-authors
The 25 scholars most cited alongside Ju Xiang, 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 91 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 76 | |
| 2 | 2011 | 51 | |
| 3 | 2016 | 49 | |
| 4 | 2006 | 47 | |
| 5 | 2015 | 45 | |
| 6 | 2019 | 42 | |
| 7 | 2023 | 38 | |
| 8 | 2021 | 32 | |
| 9 | 2020 | 32 | |
| 10 | 2016 | 26 | |
| 11 | 2017 | 26 | |
| 12 | 2020 | 26 | |
| 13 | 2020 | 25 | |
| 14 | 2015 | 25 | |
| 15 | 2012 | 23 | |
| 16 | 2013 | 22 | |
| 17 | 2018 | 21 | |
| 18 | 2021 | 21 | |
| 19 | 2017 | 21 | |
| 20 | 2017 | 21 |
About Ju Xiang
Ju Xiang is a scholar working on Molecular Biology, Statistical and Nonlinear Physics, Computational Theory and Mathematics, Finance and Cancer Research, having authored 91 papers that have together received 1.2k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (34 papers), Complex Network Analysis Techniques (22 papers), Machine Learning in Bioinformatics (16 papers), Opinion Dynamics and Social Influence (14 papers), Gene expression and cancer classification (14 papers), Computational Drug Discovery Methods (11 papers), Circular RNAs in diseases (7 papers) and Gene Regulatory Network Analysis (7 papers). The work is most often cited by research in Statistical and Nonlinear Physics (198 citations), Cancer Research (152 citations), Computational Theory and Mathematics (151 citations), Finance (84 citations) and Molecular Biology (543 citations). Ju Xiang has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Liang Tang, Jianming Li, Min Li, Ke Hu, Meihua Bao, Yiuman Tse, Xiang Qin, Fang‐Xiang Wu, Jialiang Yang and Geng Tian. Their work appears in journals such as Physica A Statistical Mechanics and its Applications, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Frontiers in Genetics, Briefings in Bioinformatics and IEEE Access.
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.