Jinfa Gu
Impact in
- Biotechnology top 5%
- Cancer Research and Treatments
- Genetics top 5%
- Virus-based gene therapy research
Papers in
- Genetics 17
- Virus-based gene therapy research 17
-
- Cancer Research and Treatments 5
- Co-authors
- Xinyuan Liu (18 shared papers)Cheng Qian (7 shared papers)Zilai Zhang (7 shared papers)Qijun Qian (5 shared papers)Liang Chu (2 shared papers)Weiguo Zou (2 shared papers)Lili Zhao (3 shared papers)Rong Amy Qi (2 shared papers)
- Journals
- Human Gene Therapy (3 papers)Cancer Biology & Therapy (2 papers)Neuroreport (2 papers)Annals of Medicine (2 papers)Nature Communications (1 paper)
- Partner nations
- ChinaSpainUnited States
In The Last Decade
Jinfa Gu
29 papers receiving 840 citations
Peers
Comparison fields: 5 of 72
- Biotechnology 137
- Genetics 403
- Oncology 258
- Cancer Research 112
- Molecular Biology 473
Countries citing papers authored by Jinfa Gu
This map shows the geographic impact of Jinfa 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 Jinfa Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jinfa Gu more than expected).
Fields of papers citing papers by Jinfa Gu
This network shows the impact of papers produced by Jinfa 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 Jinfa Gu. The network helps show where Jinfa Gu may publish in the future.
Co-authors
The 25 scholars most cited alongside Jinfa 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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 134 | |
| 2 | 2021 | 131 | |
| 3 | 2005 | 104 | |
| 4 | 2006 | 60 | |
| 5 | 2005 | 52 | |
| 6 | 2015 | 45 | |
| 7 | 2006 | 32 | |
| 8 | 2002 | 28 | |
| 9 | 2006 | 27 | |
| 10 | 2020 | 26 | |
| 11 | 2009 | 26 | |
| 12 | 2004 | 25 | |
| 13 | 2014 | 24 | |
| 14 | 2018 | 24 | |
| 15 | 2002 | 20 | |
| 16 | 2009 | 17 | |
| 17 | 2003 | 15 | |
| 18 | 2021 | 13 | |
| 19 | 2005 | 10 | |
| 20 | 2024 | 10 |
About Jinfa Gu
Jinfa Gu is a scholar working on Genetics, Biotechnology, Oncology, Molecular Biology and Pharmacology, having authored 31 papers that have together received 852 indexed citations. Recurring topics across this work include Virus-based gene therapy research (17 papers), CAR-T cell therapy research (7 papers), Cancer Research and Treatments (5 papers), Viral Infectious Diseases and Gene Expression in Insects (4 papers), Pharmacological Effects of Natural Compounds (3 papers), Cell death mechanisms and regulation (3 papers), RNA Interference and Gene Delivery (3 papers) and CRISPR and Genetic Engineering (2 papers). The work is most often cited by research in Biotechnology (137 citations), Genetics (403 citations), Oncology (258 citations), Cancer Research (112 citations) and Molecular Biology (473 citations). Jinfa Gu has collaborated with scholars based in China, Spain and United States. Frequent co-authors include Xinyuan Liu, Cheng Qian, Zilai Zhang, Qijun Qian, Liang Chu, Weiguo Zou, Lili Zhao, Rong Amy Qi, Zifei Pei and Songbo Qiu. Their work appears in journals such as Human Gene Therapy, Cancer Biology & Therapy, Neuroreport, Annals of Medicine 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.