Zu‐Guo Yu
Impact in
-
- Complex Network Analysis Techniques
- Chaos control and synchronization
- Modeling and Simulation top 2%
Papers in
-
- Machine Learning in Bioinformatics 41
- Fractal and DNA sequence analysis 38
- Genomics and Phylogenetic Studies 30
- RNA and protein synthesis mechanisms 18
- Protein Structure and Dynamics 11
-
- Chaos control and synchronization 21
- Complex Network Analysis Techniques 14
- Co-authors
- Vo Anh (59 shared papers)Ka‐Sing Lau (6 shared papers)Yu Zhou (11 shared papers)Jianyi Yang (6 shared papers)Yee Leung (6 shared papers)Chong‐Yu Xu (3 shared papers)Liqian Zhou (10 shared papers)Qiang Zhang (2 shared papers)
In The Last Decade
Zu‐Guo Yu
131 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 137
- Statistical and Nonlinear Physics 504
- Modeling and Simulation 113
- Economics and Econometrics 528
- Molecular Biology 1.1k
- Condensed Matter Physics 162
Countries citing papers authored by Zu‐Guo Yu
This map shows the geographic impact of Zu‐Guo Yu'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 Zu‐Guo Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zu‐Guo Yu more than expected).
Fields of papers citing papers by Zu‐Guo Yu
This network shows the impact of papers produced by Zu‐Guo Yu. 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 Zu‐Guo Yu. The network helps show where Zu‐Guo Yu may publish in the future.
Co-authors
The 25 scholars most cited alongside Zu‐Guo Yu, 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 139 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2003 | 103 | |
| 2 | 2009 | 91 | |
| 3 | 2013 | 76 | |
| 4 | 2008 | 73 | |
| 5 | 2003 | 62 | |
| 6 | 2008 | 56 | |
| 7 | 2015 | 54 | |
| 8 | 2023 | 53 | |
| 9 | 2000 | 53 | |
| 10 | 2014 | 49 | |
| 11 | 2010 | 40 | |
| 12 | 1996 | 39 | |
| 13 | 2005 | 37 | |
| 14 | 2006 | 37 | |
| 15 | 2004 | 36 | |
| 16 | 2017 | 35 | |
| 17 | 2017 | 35 | |
| 18 | 2014 | 34 | |
| 19 | 2016 | 31 | |
| 20 | 2002 | 30 |
About Zu‐Guo Yu
Zu‐Guo Yu is a scholar working on Molecular Biology, Statistical and Nonlinear Physics, Economics and Econometrics, Computer Networks and Communications and Genetics, having authored 139 papers that have together received 2.1k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (41 papers), Fractal and DNA sequence analysis (38 papers), Complex Systems and Time Series Analysis (33 papers), Genomics and Phylogenetic Studies (30 papers), Chaos control and synchronization (21 papers), RNA and protein synthesis mechanisms (18 papers), Complex Network Analysis Techniques (14 papers) and Protein Structure and Dynamics (11 papers). The work is most often cited by research in Statistical and Nonlinear Physics (504 citations), Modeling and Simulation (113 citations), Economics and Econometrics (528 citations), Molecular Biology (1.1k citations) and Condensed Matter Physics (162 citations). Zu‐Guo Yu has collaborated with scholars based in China, Australia and Hong Kong. Frequent co-authors include Vo Anh, Ka‐Sing Lau, Yu Zhou, Jianyi Yang, Yee Leung, Chong‐Yu Xu, Liqian Zhou, Qiang Zhang, Fu-Yao Ren and Guosheng Han. Their work appears in journals such as Physica A Statistical Mechanics and its Applications, Chaos An Interdisciplinary Journal of Nonlinear Science, Physics Letters A, Chaos Solitons & Fractals and Journal of Theoretical Biology.
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.