Shen Gu

2.8k citations
38 papers · 833 · h-index 18

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
  • Genetics top 10%
    • Genomic variations and chromosomal abnormalities
    • Genomics and Rare Diseases

Papers in

    • Genomic variations and chromosomal abnormalities 9
    • Genomics and Rare Diseases 4
    • Neurogenetic and Muscular Disorders Research 3

Shen Gu

35 papers receiving 792 citations

Peers

Shen Gu
Comparison fields: 5 of 87
  • Cancer Research 210
  • Genetics 232
  • Molecular Biology 475
  • Genetics 64
  • Plant Science 143
Replace Matilda F. Chan with:
Matilda F. Chan United States
Anna Sahakyan United States
Katherine Rhodes United States
Meromit Singer United States
Laurence Taine France
Jérôme D. Robin France
Xiaolong Liu China
Lifeng Xu United States
Seok‐Jin Heo United States
Nassim Arouche France
Shen Gu relative to Matilda F. Chan United States Matilda F. Chan's profile →
Citations per field
00.5×4.0×
Matilda F. Chan · 1×
Citations per year

Countries citing papers authored by Shen Gu

Since Specialization
Citations

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

Fields of papers citing papers by Shen Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015118
2 201577
3 201258
4 201257
5 201455
6 201851
7 201350
8 201440
9 201532
10 201629
11 201326
12 201525
13 200921
14 201920
15 201819
16 201618
17 201418
18 201617
19 201915
20 201813

About Shen Gu

Shen Gu is a scholar working on Molecular Biology, Genetics, Plant Science, Cancer Research and Genetics, having authored 38 papers that have together received 833 indexed citations. Recurring topics across this work include Genomic variations and chromosomal abnormalities (9 papers), Chromosomal and Genetic Variations (7 papers), MicroRNA in disease regulation (6 papers), Genomics and Rare Diseases (4 papers), Hereditary Neurological Disorders (3 papers), Prenatal Screening and Diagnostics (3 papers), Cancer-related molecular mechanisms research (3 papers) and Neurogenetic and Muscular Disorders Research (3 papers). The work is most often cited by research in Cancer Research (210 citations), Genetics (232 citations), Molecular Biology (475 citations), Genetics (64 citations) and Plant Science (143 citations). Shen Gu has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Wai‐Yee Chan, Bifeng Chen, Lu Li, James R. Lupski, Yick-Keung Suen, Bo Yuan, Christine R. Beck, TL Lee, Claudia M.B. Carvalho and Paweł Stankiewicz. Their work appears in journals such as Human Mutation, Scientific Reports, Human Molecular Genetics, Stem Cell Research and European Journal of Obstetrics & Gynecology and Reproductive Biology.

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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