Hua Gu

644 citations
31 papers · 404 indexed · h-index 13
Topics
Hepatitis Viruses Studies and Epidemiology (6 papers)Data-Driven Disease Surveillance (6 papers)Nonlinear Partial Differential Equations (5 papers)
Journals
SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
Partner nations
ChinaUnited StatesIndia

In The Last Decade

Hua Gu

27 papers receiving 397 citations

Peers

Hua Gu
Comparison fields: 5 of 97
  • Epidemiology 162
  • Infectious Diseases 123
  • Sociology and Political Science 86
  • Health 54
  • Modeling and Simulation 54
Replace D Fleming with:
D Fleming United Kingdom
Chaeshin Chu South Korea
Silvia Bianchi Italy
Helena Rebelo‐de‐Andrade Portugal
Adnan Khan Pakistan
Hanley J. Ho Singapore
Jean-Baptiste Meynard France
Yuanxia Cui China
Mikaela Keller United States
Emmanuel Abanida Nigeria
Hua Gu relative to D Fleming United Kingdom D Fleming's profile →
Citations per field
00.5×7.2×
D Fleming · 1×
Citations per year

Countries citing papers authored by Hua Gu

Since Specialization
Citations

This map shows the geographic impact of Hua Gu'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 Hua Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hua Gu more than expected).

Fields of papers citing papers by Hua Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hua Gu. 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 Hua Gu. The network helps show where Hua Gu may publish in the future.

Co-authorship network of co-authors of Hua Gu

This figure shows the co-authorship network connecting the top 25 collaborators of Hua Gu. A scholar is included among the top collaborators of Hua Gu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hua Gu. Hua Gu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 3
3 0
4 1
5 14
6 23
7 8
8 14
9 16
10 20
11 22
12 44
13 4
14 10
15 58
16
Existence of infinitely many periodic solutions for second-order Hamiltonian systems
2
17 4
18 9
19 0
20
[Increase of EGFR expression by Epstein-Barr virus LMP1 in nasopharyngeal carcinoma cells].
5

About Hua Gu

Hua Gu is a scholar working on Hepatology, Applied Mathematics and Epidemiology, having authored 31 papers that have together received 404 indexed citations. Recurring topics across this work include Hepatitis Viruses Studies and Epidemiology (6 papers), Data-Driven Disease Surveillance (6 papers) and Nonlinear Partial Differential Equations (5 papers). The work is most often cited by research in Modeling and Simulation (54 citations), Infectious Diseases (123 citations) and Health (54 citations). Hua Gu has collaborated with scholars based in China, United States and India. Frequent co-authors include Jianmin Jiang, Zhenggang Jiang, Bin Chen, Tianqing An, Kui Liu, Tao Jiang, Huakun Lv, Dawei Zheng, Xinyi Wang and Xiaomeng Wang. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

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.

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