Pengda Chen
Impact in
- Nephrology top 2%
- Gout, Hyperuricemia, Uric Acid
- Immunology top 2%
- interferon and immune responses
- Immune Response and Inflammation
Papers in
-
- Circular RNAs in diseases 2
- Epigenetics and DNA Methylation 1
- Ubiquitin and proteasome pathways 1
- Histone Deacetylase Inhibitors Research 1
- Co-authors
- Jiahuai Han (2 shared papers)Wanting He (2 shared papers)Lichen Hu (1 shared paper)Xin Wang (1 shared paper)Haoqiang Wan (1 shared paper)Chuan‐Qi Zhong (1 shared paper)Zhang‐Hua Yang (1 shared paper)Wenjuan Li (1 shared paper)
- Journals
- Cell Research (2 papers)Cell Reports (2 papers)Cellular and Molecular Immunology (2 papers)Cancer Letters (1 paper)Nature Communications (1 paper)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Pengda Chen
9 papers receiving 2.7k citations
Pengda Chen's Hit Papers
Peers
Comparison fields: 5 of 103
- Nephrology 293
- Immunology 864
- Molecular Biology 2.3k
- Biological Psychiatry 35
- Parasitology 84
Countries citing papers authored by Pengda Chen
This map shows the geographic impact of Pengda Chen'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 Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pengda Chen more than expected).
Fields of papers citing papers by Pengda Chen
This network shows the impact of papers produced by Pengda Chen. 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 Chen. The network helps show where Pengda Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Pengda Chen, 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 | Gasdermin D is an executor of pyroptosis and required for interleukin-1β secretion Hit paper breakdown → | 2015 | 1967 |
| 2 | Translocation of mixed lineage kinase domain-like protein to plasma membrane leads to necrotic cell death Hit paper breakdown → | 2013 | 632 |
| 3 | 2016 | 63 | |
| 4 | 2020 | 37 | |
| 5 | 2023 | 8 | |
| 6 | 2017 | 5 | |
| 7 | 2024 | 4 | |
| 8 | 2024 | 3 | |
| 9 | 2025 | 1 |
About Pengda Chen
Pengda Chen is a scholar working on Molecular Biology, Immunology, Cancer Research, Nephrology and Mechanics of Materials, having authored 9 papers that have together received 2.7k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (3 papers), Circular RNAs in diseases (2 papers), Cancer-related molecular mechanisms research (2 papers), Genetics and Neurodevelopmental Disorders (1 paper), Epigenetics and DNA Methylation (1 paper), Ubiquitin and proteasome pathways (1 paper), Fatigue and fracture mechanics (1 paper) and Histone Deacetylase Inhibitors Research (1 paper). The work is most often cited by research in Nephrology (293 citations), Immunology (864 citations), Molecular Biology (2.3k citations), Biological Psychiatry (35 citations) and Parasitology (84 citations). Pengda Chen has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Jiahuai Han, Wanting He, Lichen Hu, Xin Wang, Haoqiang Wan, Chuan‐Qi Zhong, Zhang‐Hua Yang, Wenjuan Li, Junming Ren and Xin Chen. Their work appears in journals such as Cell Research, Cell Reports, Cellular and Molecular Immunology, Cancer Letters 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.