Jun Xie
Impact in
- Hepatology top 2%
- Hepatitis Viruses Studies and Epidemiology
- Liver Disease and Transplantation
- Genetics top 2%
- Virus-based gene therapy research
Papers in
-
- RNA Interference and Gene Delivery 15
- CRISPR and Genetic Engineering 15
- Plant Gene Expression Analysis 5
- Genetics 29
- Virus-based gene therapy research 27
- Co-authors
- Guangping Gao (48 shared papers)Qin Su (12 shared papers)Dan Wang (10 shared papers)Phillip W.L. Tai (13 shared papers)Terence R. Flotte (7 shared papers)Jae‐Hyuck Shim (8 shared papers)Yeon-Suk Yang (8 shared papers)Hongwei Zhang (4 shared papers)
- Journals
- Molecular Therapy — Methods & Clinical Development (8 papers)Human Gene Therapy (7 papers)Molecular Therapy (6 papers)Nature Communications (5 papers)Microbial Pathogenesis (2 papers)
- Partner nations
- United StatesChinaSouth Korea
In The Last Decade
Jun Xie
81 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 120
- Hepatology 265
- Genetics 761
- Cancer Research 359
- Molecular Biology 1.4k
- Infectious Diseases 317
Countries citing papers authored by Jun Xie
This map shows the geographic impact of Jun Xie'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 Jun Xie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Xie more than expected).
Fields of papers citing papers by Jun Xie
This network shows the impact of papers produced by Jun Xie. 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 Jun Xie. The network helps show where Jun Xie may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Xie, 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 83 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 213 | |
| 2 | 2012 | 177 | |
| 3 | 2010 | 138 | |
| 4 | 2017 | 118 | |
| 5 | 2019 | 102 | |
| 6 | 2022 | 87 | |
| 7 | 2023 | 85 | |
| 8 | 2013 | 78 | |
| 9 | 2017 | 76 | |
| 10 | 2018 | 69 | |
| 11 | 2015 | 62 | |
| 12 | 2014 | 61 | |
| 13 | 2018 | 55 | |
| 14 | 2019 | 54 | |
| 15 | 2022 | 47 | |
| 16 | 2018 | 45 | |
| 17 | 2020 | 41 | |
| 18 | 2021 | 40 | |
| 19 | 2022 | 40 | |
| 20 | 2019 | 39 |
About Jun Xie
Jun Xie is a scholar working on Molecular Biology, Genetics, Plant Science, Infectious Diseases and Immunology, having authored 83 papers that have together received 2.5k indexed citations. Recurring topics across this work include Virus-based gene therapy research (27 papers), RNA Interference and Gene Delivery (15 papers), CRISPR and Genetic Engineering (15 papers), Viral gastroenteritis research and epidemiology (8 papers), MicroRNA in disease regulation (6 papers), Plant Gene Expression Analysis (5 papers), Viral Infections and Immunology Research (5 papers) and interferon and immune responses (4 papers). The work is most often cited by research in Hepatology (265 citations), Genetics (761 citations), Cancer Research (359 citations), Molecular Biology (1.4k citations) and Infectious Diseases (317 citations). Jun Xie has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include Guangping Gao, Qin Su, Dan Wang, Phillip W.L. Tai, Terence R. Flotte, Jae‐Hyuck Shim, Yeon-Suk Yang, Hongwei Zhang, Jung‐Min Kim and Qing Xie. Their work appears in journals such as Molecular Therapy — Methods & Clinical Development, Human Gene Therapy, Molecular Therapy, Nature Communications and Microbial Pathogenesis.
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.