Ge Guan

586 total citations
23 papers, 472 citations indexed

About

Ge Guan is a scholar working on Molecular Biology, Surgery and Biomaterials. According to data from OpenAlex, Ge Guan has authored 23 papers receiving a total of 472 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 7 papers in Surgery and 5 papers in Biomaterials. Recurrent topics in Ge Guan's work include Tissue Engineering and Regenerative Medicine (5 papers), Electrospun Nanofibers in Biomedical Applications (5 papers) and Graphene and Nanomaterials Applications (4 papers). Ge Guan is often cited by papers focused on Tissue Engineering and Regenerative Medicine (5 papers), Electrospun Nanofibers in Biomedical Applications (5 papers) and Graphene and Nanomaterials Applications (4 papers). Ge Guan collaborates with scholars based in China, United States and Canada. Ge Guan's co-authors include Chuhong Zhu, Wen Zeng, Ju Tan, Yanzhao Li, Ning Ding, Keyu Wei, Panke Cheng, Feila Liu, Da Huo and Mingcan Yang and has published in prestigious journals such as SHILAP Revista de lepidopterología, ACS Nano and The Science of The Total Environment.

In The Last Decade

Ge Guan

22 papers receiving 469 citations

Peers

Ge Guan
Comparison fields: 5 of 92
  • Molecular Biology 148
  • Biomedical Engineering 119
  • Biomaterials 113
  • Surgery 110
  • Immunology 62
Replace Wanjin Tang with:
Wanjin Tang United States
Yunpeng Zhao China
Yi Ou China
Markus Absenger Austria
Xiyue Li China
Radwa A. Mehanna Egypt
Maria Rosaria Ambrosio Italy
Guoqiang Liu United States
Qingyun Xie China
Jimin Long China
Wanjin Tang United States View profile →
Citations per field, relative to Ge Guan
Ge Guan · 1×
Citations per year, relative to Ge Guan
Ge Guan · 1×

Countries citing papers authored by Ge Guan

Since Specialization
Citations

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

Fields of papers citing papers by Ge Guan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ge Guan

This figure shows the co-authorship network connecting the top 25 collaborators of Ge Guan. A scholar is included among the top collaborators of Ge Guan 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 Ge Guan. Ge Guan 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
# Work Indexed citations
1 0
2 5
3 65
4 4
5 8
6 19
7 23
8 20
9 2
10
IFI30 Is a Novel Immune-Related Target with Predicting Value of Prognosis and Treatment Response in Glioblastoma
2
11
Secretory Pathway Kinase FAM20C, a Marker for Glioma Invasion and Malignancy, Predicts Poor Prognosis of Glioma
1
12 12
13 3
14 9
15 25
16 24
17 28
18 64
19 36
20 34

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026