Pengda Liu
Impact in
- Molecular Biology top 2%
- Ubiquitin and proteasome pathways
- PI3K/AKT/mTOR signaling in cancer
- RNA modifications and cancer
- Protein Degradation and Inhibitors
- RNA Research and Splicing
- Cancer Research top 2%
Papers in
-
- Ubiquitin and proteasome pathways 27
- PI3K/AKT/mTOR signaling in cancer 13
- Protein Degradation and Inhibitors 9
- RNA modifications and cancer 8
- Cell Biology 13
- Microtubule and mitosis dynamics 7
- Journals
- Molecular Cell (4 papers)Oncotarget (4 papers)Advanced Science (3 papers)Journal of Materials Chemistry A (3 papers)Nature Communications (2 papers)
- Partner nations
- United StatesChinaGermany
In The Last Decade
Pengda Liu
74 papers receiving 4.6k citations
Hit Papers
Peers
Comparison fields: 5 of 136
- Molecular Biology 3.4k
- Cancer Research 670
- Oncology 996
- Immunology 672
- Cell Biology 488
Countries citing papers authored by Pengda Liu
This map shows the geographic impact of Pengda Liu'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 Pengda Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pengda Liu more than expected).
Fields of papers citing papers by Pengda Liu
This network shows the impact of papers produced by Pengda Liu. 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 Pengda Liu. The network helps show where Pengda Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Pengda Liu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 4 | |
| 5 | 2023 | 2 | |
| 6 | 2023 | 1 | |
| 7 | 2023 | 14 | |
| 8 | 2022 | 8 | |
| 9 | 2021 | 2 | |
| 10 | 2020 | 164 | |
| 11 | 2020 | 27 | |
| 12 | 2020 | 15 | |
| 13 | 2019 | 24 | |
| 14 | 2019 | 34 | |
| 15 | 2017 | 1 | |
| 16 | 2016 | 89 | |
| 17 | 2015 | 307 | |
| 18 | SPOP Promotes Ubiquitination and Degradation of the ERG Oncoprotein to Suppress Prostate Cancer Progression | 2015 | 1 |
| 19 | Roles of F-box proteins in cancer Hit paper breakdown → | 2014 | 407 |
| 20 | 2011 | 96 |
About Pengda Liu
Pengda Liu is a scholar working on Molecular Biology, Cell Biology, Immunology, Oncology and Geriatrics and Gerontology, having authored 79 papers that have together received 4.7k indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (27 papers), interferon and immune responses (13 papers), PI3K/AKT/mTOR signaling in cancer (13 papers), Cancer-related Molecular Pathways (10 papers), Protein Degradation and Inhibitors (9 papers), RNA modifications and cancer (8 papers), Microtubule and mitosis dynamics (7 papers) and Metal-Organic Frameworks: Synthesis and Applications (7 papers). The work is most often cited by research in Molecular Biology (3.4k citations), Cancer Research (670 citations), Oncology (996 citations), Immunology (672 citations) and Cell Biology (488 citations). Pengda Liu has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Wenyi Wei, Le Yu, Hiroyuki Inuzuka, Zhiwei Wang, Jessica Wei, Wenjian Gan, Daming Gao, Jianping Guo, Lixin Wan and Alex Toker. Their work appears in journals such as Molecular Cell, Oncotarget, Advanced Science, Journal of Materials Chemistry A 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.