Ge Hu
Impact in
-
- Computational Drug Discovery Methods
- Pharmacology top 10%
- Cholinesterase and Neurodegenerative Diseases
Papers in
-
- Gut microbiota and health 3
- Protein Structure and Dynamics 3
- Receptor Mechanisms and Signaling 2
- Epidemiology 12
- Influenza Virus Research Studies 7
- Pneumonia and Respiratory Infections 4
- Co-authors
- Jun Xu (15 shared papers)Qiong Gu (9 shared papers)Xiang Mu (15 shared papers)Hong Dong (10 shared papers)Tao Zhang (13 shared papers)Xin Yan (2 shared papers)Wenxia Zhao (4 shared papers)Rui Pang (1 shared paper)
- Journals
- Journal of Chemical Information and Modeling (5 papers)RSC Advances (2 papers)Scientific Reports (2 papers)Molecular Diversity (2 papers)Viruses (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Ge Hu
71 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 114
- Computational Theory and Mathematics 168
- Pharmacology 71
- Pharmacology 125
- Complementary and alternative medicine 60
- Molecular Biology 425
Countries citing papers authored by Ge Hu
This map shows the geographic impact of Ge Hu'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 Ge Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ge Hu more than expected).
Fields of papers citing papers by Ge Hu
This network shows the impact of papers produced by Ge Hu. 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 Ge Hu. The network helps show where Ge Hu may publish in the future.
Co-authors
The 25 scholars most cited alongside Ge Hu, 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 77 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 105 | |
| 2 | 2013 | 73 | |
| 3 | 2016 | 69 | |
| 4 | 2013 | 68 | |
| 5 | 2021 | 59 | |
| 6 | 2013 | 56 | |
| 7 | 2013 | 53 | |
| 8 | 2005 | 40 | |
| 9 | 2014 | 34 | |
| 10 | 2012 | 30 | |
| 11 | 2011 | 30 | |
| 12 | 2011 | 28 | |
| 13 | 2012 | 27 | |
| 14 | 2018 | 25 | |
| 15 | 2024 | 24 | |
| 16 | 2017 | 24 | |
| 17 | 2017 | 23 | |
| 18 | 2014 | 18 | |
| 19 | 2014 | 18 | |
| 20 | 2020 | 15 |
About Ge Hu
Ge Hu is a scholar working on Molecular Biology, Epidemiology, Immunology, Pulmonary and Respiratory Medicine and Oncology, having authored 77 papers that have together received 1.1k indexed citations. Recurring topics across this work include Immune Response and Inflammation (8 papers), Influenza Virus Research Studies (7 papers), Computational Drug Discovery Methods (6 papers), Pneumonia and Respiratory Infections (4 papers), Gut microbiota and health (3 papers), interferon and immune responses (3 papers), Protein Structure and Dynamics (3 papers) and Receptor Mechanisms and Signaling (2 papers). The work is most often cited by research in Computational Theory and Mathematics (168 citations), Pharmacology (71 citations), Pharmacology (125 citations), Complementary and alternative medicine (60 citations) and Molecular Biology (425 citations). Ge Hu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Jun Xu, Qiong Gu, Xiang Mu, Hong Dong, Tao Zhang, Xin Yan, Wenxia Zhao, Rui Pang, Meng Chen and Zhihong Liu. Their work appears in journals such as Journal of Chemical Information and Modeling, RSC Advances, Scientific Reports, Molecular Diversity and Viruses.
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.