Pengda Chen
Impact in
- Molecular Biology top 2%
- Inflammasome and immune disorders
- Cell death mechanisms and regulation
- Immunology top 10%
- Immune Response and Inflammation
- interferon and immune responses
Papers in
-
- MicroRNA in disease regulation 4
-
- T-cell and B-cell Immunology 3
- Co-authors
- Wanting He (2 shared papers)Jiahuai Han (2 shared papers)Lichen Hu (1 shared paper)Zhang‐Hua Yang (1 shared paper)Chuan‐Qi Zhong (1 shared paper)Haoqiang Wan (1 shared paper)Xin Wang (1 shared paper)Xin Chen (1 shared paper)
- Journals
- Cellular and Molecular Immunology (2 papers)Cell Reports (2 papers)Cell Research (2 papers)Nature Immunology (1 paper)Science Advances (1 paper)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Pengda Chen
12 papers receiving 2.9k citations
Pengda Chen's Hit Papers
Peers
Comparison fields: 5 of 91
- Molecular Biology 2.1k
- Immunology 264
- Cancer Research 126
- Neurology 66
- Nephrology 57
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 | 2098 |
| 2 | Translocation of mixed lineage kinase domain-like protein to plasma membrane leads to necrotic cell death Hit paper breakdown → | 2013 | 681 |
| 3 | 2016 | 70 | |
| 4 | 2020 | 41 | |
| 5 | 2017 | 34 | |
| 6 | 2023 | 9 | |
| 7 | 2018 | 8 | |
| 8 | 2024 | 8 | |
| 9 | 2021 | 7 | |
| 10 | 2024 | 6 | |
| 11 | 2025 | 2 | |
| 12 | 2026 | 1 |
About Pengda Chen
Pengda Chen is a scholar working on Cancer Research, Immunology, Molecular Biology, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 12 papers that have together received 3k indexed citations. Recurring topics across this work include MicroRNA in disease regulation (4 papers), T-cell and B-cell Immunology (3 papers), Epigenetics and DNA Methylation (1 paper), RNA and protein synthesis mechanisms (1 paper), Inflammasome and immune disorders (1 paper), Cell death mechanisms and regulation (1 paper), RNA Research and Splicing (1 paper) and Wnt/β-catenin signaling in development and cancer (1 paper). The work is most often cited by research in Molecular Biology (2.1k citations), Immunology (264 citations), Cancer Research (126 citations), Neurology (66 citations) and Nephrology (57 citations). Pengda Chen has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Wanting He, Jiahuai Han, Lichen Hu, Zhang‐Hua Yang, Chuan‐Qi Zhong, Haoqiang Wan, Xin Wang, Xin Chen, Junming Ren and Wenjuan Li. Their work appears in journals such as Cellular and Molecular Immunology, Cell Reports, Cell Research, Nature Immunology and Science Advances.
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.