Ge Hu

1.3k citations
77 papers · 1.0k · h-index 18

Impact in

Papers in

    • Gut microbiota and health 3
    • Protein Structure and Dynamics 3
    • Receptor Mechanisms and Signaling 2
    • Influenza Virus Research Studies 7
    • Pneumonia and Respiratory Infections 4

Ge Hu

71 papers receiving 1.0k citations

Peers

Ge Hu
Comparison fields: 5 of 112
  • Computational Theory and Mathematics 157
  • Pharmacology 69
  • Complementary and alternative medicine 59
  • Pharmacology 120
  • Molecular Biology 412
Replace Sarah Albogami with:
Sarah Albogami Saudi Arabia
Zhenquan Hu China
Ghulam Mustafa Pakistan
Katrin Stierand Germany
Bader Alshehri Saudi Arabia
Ramakrishna Vadde India
Foysal Ahammad Saudi Arabia
Qi Zhou China
Keng‐Chang Tsai Taiwan
Ge Hu relative to Sarah Albogami Saudi Arabia Sarah Albogami's profile →
Citations per field
00.5×10×16×
Sarah Albogami · 1×
Citations per year

Countries citing papers authored by Ge Hu

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Ge Hu Line = papers co-authored together Ge Hu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 77 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010103
2 201369
3 201668
4 201366
5 202159
6 201355
7 201349
8 200539
9 201432
10 201230
11 201130
12 201127
13 201225
14 201825
15 202424
16 201723
17 201722
18 201418
19 201416
20 202015

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 1.0k 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 (157 citations), Pharmacology (69 citations), Complementary and alternative medicine (59 citations), Pharmacology (120 citations) and Molecular Biology (412 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, Zhihong Liu, Jiabo Li, Minghao Zheng and Wenxia Zhao. Their work appears in journals such as Journal of Chemical Information and Modeling, Insights into Imaging, Viruses, Virology Journal and Frontiers in Medicine.

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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