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
- Wanting He (2 shared papers)Jiahuai Han (2 shared papers)Zhang‐Hua Yang (1 shared paper)Chuan‐Qi Zhong (1 shared paper)Lichen Hu (1 shared paper)Haoqiang Wan (1 shared paper)Xin Wang (1 shared paper)Chao Yang (1 shared paper)
- Journals
- Cell Research (2 papers)Cell Reports (2 papers)Cellular and Molecular Immunology (2 papers)Nature Communications (1 paper)Cancer Letters (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 294
- Immunology 876
- Molecular Biology 2.3k
- Biological Psychiatry 36
- 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 | 1987 |
| 2 | Translocation of mixed lineage kinase domain-like protein to plasma membrane leads to necrotic cell death Hit paper breakdown → | 2013 | 651 |
| 3 | 2016 | 67 | |
| 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 2.8k 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 (294 citations), Immunology (876 citations), Molecular Biology (2.3k citations), Biological Psychiatry (36 citations) and Parasitology (84 citations). Pengda Chen has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Wanting He, Jiahuai Han, Zhang‐Hua Yang, Chuan‐Qi Zhong, Lichen Hu, Haoqiang Wan, Xin Wang, Chao Yang, Deli Huang and Yunlong Song. Their work appears in journals such as Cell Research, Cell Reports, Cellular and Molecular Immunology, Nature Communications and Cancer Letters.
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.