Lin Gu

925 citations
48 papers · 725 · h-index 16

Impact in

  • Hepatology top 5%
    • Hepatitis C virus research
    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research

Papers in

    • Hepatitis B Virus Studies 19
    • Liver Disease Diagnosis and Treatment 10
    • Hepatitis C virus research 19
    • Hepatitis Viruses Studies and Epidemiology 3

Lin Gu

47 papers receiving 715 citations

Peers

Lin Gu
Comparison fields: 5 of 83
  • Hepatology 160
  • Cancer Research 196
  • Reproductive Medicine 107
  • Obstetrics and Gynecology 72
  • Immunology 148
Replace Yoko Aoyagi with:
Yoko Aoyagi Japan
Ngai Na Co Hong Kong
Wanhua Ren China
Qiuhong Liu China
Xiaohui Tian China
Elham Hassen Tunisia
Yan Tang China
Shiqiu Xiong China
G Korczak-Kowalska Poland
Lin Gu relative to Yoko Aoyagi Japan Yoko Aoyagi's profile →
Citations per field
00.5×1.5×1.9×
Yoko Aoyagi · 1×
Citations per year

Countries citing papers authored by Lin Gu

Since Specialization
Citations

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

Fields of papers citing papers by Lin Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201362
2 201356
3 200851
4 201750
5 201747
6 201838
7 201535
8 201930
9 201829
10 200626
11 201725
12 201822
13 201318
14 202017
15 201316
16 201916
17 201915
18 201414
19 201313
20 201313

About Lin Gu

Lin Gu is a scholar working on Epidemiology, Hepatology, Molecular Biology, Oncology and Cancer Research, having authored 48 papers that have together received 725 indexed citations. Recurring topics across this work include Hepatitis B Virus Studies (19 papers), Hepatitis C virus research (19 papers), Liver Disease Diagnosis and Treatment (10 papers), Breast Cancer Treatment Studies (5 papers), MicroRNA in disease regulation (4 papers), HER2/EGFR in Cancer Research (3 papers), Immune Cell Function and Interaction (3 papers) and Hepatitis Viruses Studies and Epidemiology (3 papers). The work is most often cited by research in Hepatology (160 citations), Cancer Research (196 citations), Reproductive Medicine (107 citations), Obstetrics and Gynecology (72 citations) and Immunology (148 citations). Lin Gu has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Yuehua Huang, Lubiao Chen, Yingli Shi, Jie Chen, Yurong Gu, Xirong Guo, Liang Zhou, Xiaoyan Shi, Yifan Lian and Xishan Hao. Their work appears in journals such as Scientific Reports, BMC Infectious Diseases, Cellular Physiology and Biochemistry, Oncotarget and Breast Cancer Research and Treatment.

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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