Deyong Ye
Impact in
- Toxicology top 5%
- Bioactive Compounds and Antitumor Agents
- Organic Chemistry top 10%
- Synthesis and biological activity
- Multicomponent Synthesis of Heterocycles
Papers in
-
- Sphingolipid Metabolism and Signaling 15
- Wnt/β-catenin signaling in development and cancer 5
- Ubiquitin and proteasome pathways 4
- PI3K/AKT/mTOR signaling in cancer 4
- Co-authors
- Lu Zhou (19 shared papers)Yong Chu (15 shared papers)Xian‐Cheng Jiang (6 shared papers)Renxiao Wang (3 shared papers)Ya Zhang (2 shared papers)Kaiqing Ma (3 shared papers)Ke Huang (4 shared papers)Lulu Jiang (5 shared papers)
- Journals
- European Journal of Medicinal Chemistry (8 papers)Bioorganic & Medicinal Chemistry Letters (5 papers)Tetrahedron Letters (4 papers)Bioorganic & Medicinal Chemistry (4 papers)Molecules (4 papers)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Deyong Ye
52 papers receiving 781 citations
Peers
Comparison fields: 5 of 81
- Toxicology 39
- Organic Chemistry 248
- Molecular Biology 445
- Biochemistry 28
- Physiology 91
Countries citing papers authored by Deyong Ye
This map shows the geographic impact of Deyong Ye'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 Deyong Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deyong Ye more than expected).
Fields of papers citing papers by Deyong Ye
This network shows the impact of papers produced by Deyong Ye. 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 Deyong Ye. The network helps show where Deyong Ye may publish in the future.
Co-authors
The 25 scholars most cited alongside Deyong Ye, 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 54 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 66 | |
| 2 | 2008 | 57 | |
| 3 | 2011 | 55 | |
| 4 | 2012 | 35 | |
| 5 | 2013 | 30 | |
| 6 | 2012 | 29 | |
| 7 | 2013 | 28 | |
| 8 | 2014 | 27 | |
| 9 | 2014 | 27 | |
| 10 | 1997 | 25 | |
| 11 | 2019 | 24 | |
| 12 | 2018 | 24 | |
| 13 | 2018 | 22 | |
| 14 | 2018 | 20 | |
| 15 | 2015 | 19 | |
| 16 | 2014 | 17 | |
| 17 | 2012 | 17 | |
| 18 | 2010 | 16 | |
| 19 | 2020 | 15 | |
| 20 | 2021 | 15 |
About Deyong Ye
Deyong Ye is a scholar working on Molecular Biology, Organic Chemistry, Physiology, Cancer Research and Oncology, having authored 54 papers that have together received 791 indexed citations. Recurring topics across this work include Sphingolipid Metabolism and Signaling (15 papers), Wnt/β-catenin signaling in development and cancer (5 papers), Computational Drug Discovery Methods (5 papers), Caveolin-1 and cellular processes (5 papers), Ubiquitin and proteasome pathways (4 papers), Hepatitis C virus research (4 papers), PI3K/AKT/mTOR signaling in cancer (4 papers) and Cancer, Hypoxia, and Metabolism (4 papers). The work is most often cited by research in Toxicology (39 citations), Organic Chemistry (248 citations), Molecular Biology (445 citations), Biochemistry (28 citations) and Physiology (91 citations). Deyong Ye has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Lu Zhou, Yong Chu, Xian‐Cheng Jiang, Renxiao Wang, Ya Zhang, Kaiqing Ma, Ke Huang, Lulu Jiang, Calvin Yeang and Shweta Varshney. Their work appears in journals such as European Journal of Medicinal Chemistry, Bioorganic & Medicinal Chemistry Letters, Tetrahedron Letters, Bioorganic & Medicinal Chemistry and Molecules.
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.