Bin Gan

1.0k citations
33 papers · 742 · h-index 14

Impact in

  • Cell Biology top 10%
    • Cellular transport and secretion
    • Endoplasmic Reticulum Stress and Disease
  • Physiology top 10%

Papers in

Bin Gan

32 papers receiving 734 citations

Peers

Bin Gan
Comparison fields: 5 of 102
  • Cell Biology 166
  • Physiology 34
  • Molecular Biology 409
  • Cancer Research 78
  • Immunology 106
Replace Patricia Parsons‐Wingerter with:
Patricia Parsons‐Wingerter United States
Elisa Roztocil United States
Marina Shkreli France
David S. Moons United States
Zengdun Shi United States
Qinghang Meng United States
Zhongxian Lu China
Jun Ding China
Jianyu Liu China
Katsumi Yabusaki Japan
Bin Gan relative to Patricia Parsons‐Wingerter United States Patricia Parsons‐Wingerter's profile →
Citations per field
00.5×1.5×2.4×
Patricia Parsons‐Wingerter · 1×
Citations per year

Countries citing papers authored by Bin Gan

Since Specialization
Citations

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

Fields of papers citing papers by Bin Gan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Bin Gan, 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 Bin Gan Line = papers co-authored together Bin Gan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011101
2 200783
3 200478
4 200677
5 200554
6 201941
7 202136
8 201236
9 201935
10 200730
11 201418
12 202318
13 201017
14 201315
15 202012
16 200511
17
Low-dose tubacin promotes BMSCs proliferation and morphological changes through the ERK pathway.
201911
18 202211
19 20109
20 20248

About Bin Gan

Bin Gan is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Oncology, Cell Biology and Physiology, having authored 33 papers that have together received 742 indexed citations. Recurring topics across this work include Lung Cancer Treatments and Mutations (7 papers), Cellular transport and secretion (5 papers), Gene expression and cancer classification (4 papers), Galectins and Cancer Biology (3 papers), Protein Tyrosine Phosphatases (3 papers), Lung Cancer Research Studies (3 papers), Lung Cancer Diagnosis and Treatment (3 papers) and Erythrocyte Function and Pathophysiology (2 papers). The work is most often cited by research in Cell Biology (166 citations), Physiology (34 citations), Molecular Biology (409 citations), Cancer Research (78 citations) and Immunology (106 citations). Bin Gan has collaborated with scholars based in China, Singapore and Finland. Frequent co-authors include Bor Luen Tang, Ke Guo, Christelle En Lin Chua, Jing Tang, Jie Li, Qi Zeng, Qi Zeng, Jie Li, Chun-Hou Zheng and Haihe Wang. Their work appears in journals such as Cancer Research, Clinical Cancer Research, Saudi Pharmaceutical Journal, Journal of Thoracic Oncology and Journal of Cellular Physiology.

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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