Fei Gu

4.6k citations
96 papers · 3.2k · h-index 31

Impact in

    • Protease and Inhibitor Mechanisms
    • Congenital heart defects research
    • RNA modifications and cancer
    • Epigenetics and DNA Methylation

Papers in

    • Epigenetics and DNA Methylation 10
    • Signaling Pathways in Disease 7
    • Congenital heart defects research 5
    • Genomics and Chromatin Dynamics 5
    • Machine Learning in Bioinformatics 5
    • Peptidase Inhibition and Analysis 9

Fei Gu

91 papers receiving 3.1k citations

Peers

Fei Gu
Comparison fields: 5 of 132
  • Cancer Research 647
  • Molecular Biology 1.8k
  • Genetics 235
  • Cell Biology 338
  • Oncology 452
Replace Javier Hernández‐Losa with:
Javier Hernández‐Losa Spain
Jing Pan United States
Sándor Paku Hungary
Louis Chesler United Kingdom
Kristiina Iljin Finland
Mariona Graupera Spain
Paul Dowling Ireland
Bassem R. Haddad United States
Benjamin D. Hopkins United States
Bangyan L. Stiles United States
Fei Gu relative to Javier Hernández‐Losa Spain Javier Hernández‐Losa's profile →
Citations per field
00.5×2.6×
Javier Hernández‐Losa · 1×
Citations per year

Countries citing papers authored by Fei Gu

Since Specialization
Citations

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

Fields of papers citing papers by Fei Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 96 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014337
2 2014257
3 2019218
4 2014131
5 2013101
6 201797
7 201295
8 201987
9 201487
10 200086
11 199979
12 201074
13 199871
14 199871
15 200659
16 199957
17 200156
18 201755
19 201152
20 201451

About Fei Gu

Fei Gu is a scholar working on Molecular Biology, Oncology, Cancer Research, Genetics and Pathology and Forensic Medicine, having authored 96 papers that have together received 3.2k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (10 papers), Protease and Inhibitor Mechanisms (9 papers), Peptidase Inhibition and Analysis (9 papers), Signaling Pathways in Disease (7 papers), Congenital heart defects research (5 papers), Genomics and Chromatin Dynamics (5 papers), Machine Learning in Bioinformatics (5 papers) and Mesenchymal stem cell research (4 papers). The work is most often cited by research in Cancer Research (647 citations), Molecular Biology (1.8k citations), Genetics (235 citations), Cell Biology (338 citations) and Oncology (452 citations). Fei Gu has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include William T. Pu, Qing Ma, Pingzhu Zhou, Zhiqiang Lin, Jinghai Chen, Da‐Zhi Wang, Lingyun Sun, Alexander von Gise, Stanisław Pikul and Bin Zhou. Their work appears in journals such as Journal of Medicinal Chemistry, Oncogene, Scientific Reports, Circulation Research and Nature Communications.

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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