Shuo Gu
Impact in
- Cancer Research top 2%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Molecular Biology top 5%
- RNA Interference and Gene Delivery
- RNA Research and Splicing
- RNA modifications and cancer
- Circular RNAs in diseases
- Advanced biosensing and bioanalysis techniques
- RNA and protein synthesis mechanisms
Papers in
-
- RNA Research and Splicing 16
- RNA Interference and Gene Delivery 14
- RNA modifications and cancer 7
- RNA and protein synthesis mechanisms 5
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- MicroRNA in disease regulation 21
- Cancer-related molecular mechanisms research 6
- Co-authors
- Mark A. Kay (8 shared papers)Lan Jin (7 shared papers)Feijie Zhang (6 shared papers)Xavier Bofill‐De Ros (10 shared papers)Peter Sarnow (1 shared paper)Yong Huang (5 shared papers)Acong Yang (12 shared papers)Paul N. Valdmanis (3 shared papers)
- Journals
- Nucleic Acids Research (5 papers)Nature Communications (3 papers)Cell (2 papers)RNA (2 papers)Bioinformatics (2 papers)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Shuo Gu
60 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 110
- Cancer Research 876
- Molecular Biology 1.4k
- Aging 17
- Virology 23
- Genetics 124
Countries citing papers authored by Shuo Gu
This map shows the geographic impact of Shuo 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 Shuo Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuo Gu more than expected).
Fields of papers citing papers by Shuo Gu
This network shows the impact of papers produced by Shuo 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 Shuo Gu. The network helps show where Shuo Gu may publish in the future.
Co-authors
The 25 scholars most cited alongside Shuo Gu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 361 | |
| 2 | 2012 | 239 | |
| 3 | 2010 | 149 | |
| 4 | 2019 | 67 | |
| 5 | 2011 | 65 | |
| 6 | 2012 | 61 | |
| 7 | 2016 | 61 | |
| 8 | 2020 | 55 | |
| 9 | 2015 | 48 | |
| 10 | 2019 | 47 | |
| 11 | 2019 | 46 | |
| 12 | 2016 | 40 | |
| 13 | 2016 | 37 | |
| 14 | 2011 | 33 | |
| 15 | 2021 | 31 | |
| 16 | 2019 | 30 | |
| 17 | 2004 | 27 | |
| 18 | 2022 | 27 | |
| 19 | 2016 | 27 | |
| 20 | 2014 | 24 |
About Shuo Gu
Shuo Gu is a scholar working on Molecular Biology, Cancer Research, Surgery, Computational Theory and Mathematics and Infectious Diseases, having authored 63 papers that have together received 1.9k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (21 papers), RNA Research and Splicing (16 papers), RNA Interference and Gene Delivery (14 papers), RNA modifications and cancer (7 papers), Cancer-related molecular mechanisms research (6 papers), RNA and protein synthesis mechanisms (5 papers), Computational Drug Discovery Methods (4 papers) and Bladder and Urothelial Cancer Treatments (3 papers). The work is most often cited by research in Cancer Research (876 citations), Molecular Biology (1.4k citations), Aging (17 citations), Virology (23 citations) and Genetics (124 citations). Shuo Gu has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Mark A. Kay, Lan Jin, Feijie Zhang, Xavier Bofill‐De Ros, Peter Sarnow, Yong Huang, Acong Yang, Paul N. Valdmanis, Yue Zhang and Dirk Grimm. Their work appears in journals such as Nucleic Acids Research, Nature Communications, Cell, RNA and Bioinformatics.
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.