Jing Shen
- Co-authors
- Guochang GuHaibo LiuHualong YuJing ZhaoHongde QinC. F. DeweyFrancis W. LuscinskasMichael A. Gimbrone
- Topics
- Gene expression and cancer classification (4 papers)Machine Learning in Bioinformatics (3 papers)Bioinformatics and Genomic Networks (3 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Jing Shen
18 papers receiving 298 citations
Peers
Comparison fields: 5 of 81
- Molecular Biology 156
- Artificial Intelligence 50
- Computational Mechanics 42
- Physiology 36
- Ocean Engineering 32
Countries citing papers authored by Jing Shen
This map shows the geographic impact of Jing Shen'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 Jing Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jing Shen more than expected).
Fields of papers citing papers by Jing Shen
This network shows the impact of papers produced by Jing Shen. 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 Jing Shen. The network helps show where Jing Shen may publish in the future.
Co-authorship network of co-authors of Jing Shen
This figure shows the co-authorship network connecting the top 25 collaborators of Jing Shen. A scholar is included among the top collaborators of Jing Shen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jing Shen. Jing Shen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 17 | |
| 3 | PKI-587 enhances chemosensitivity of oxaliplatin in hepatocellular carcinoma through suppressing DNA damage repair pathway (NHEJ and HR) and PI3K/AKT/mTOR pathway. | 36 |
| 4 | BEZ235 enhances chemosensitivity of paclitaxel in hepatocellular carcinoma through inhibiting the PI3K/Akt/mTOR pathway. | 20 |
| 5 | 64 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 8 | |
| 9 | Review of water entry problem | 5 |
| 10 | 34 | |
| 11 | 1 | |
| 12 | 65 | |
| 13 | 7 | |
| 14 | 1 | |
| 15 | Relationship between polymorphism of E-cadherin gene and genetic susceptibility of non-cardia gastric cancer | 1 |
| 16 | 5 | |
| 17 | Multi-AUV 3D-Simulation Based on CADCON | 1 |
| 18 | 1 | |
| 19 | 36 |
About Jing Shen
Jing Shen is a scholar working on Ocean Engineering, Physiology and Biochemistry, having authored 19 papers that have together received 304 indexed citations. Recurring topics across this work include Gene expression and cancer classification (4 papers), Machine Learning in Bioinformatics (3 papers) and Bioinformatics and Genomic Networks (3 papers). The work is most often cited by research in Molecular Biology (156 citations), Ocean Engineering (32 citations) and Computational Mechanics (42 citations). Jing Shen has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Guochang Gu, Haibo Liu, Hualong Yu, Jing Zhao, Hongde Qin, C. F. Dewey, Francis W. Luscinskas, Michael A. Gimbrone, Rituraj Khound and Jens Walter. Their work appears in journals such as Blood, Biophysical Journal and Arteriosclerosis Thrombosis and Vascular 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.