Pengda Chen

3.4k total citations · 2 hit papers
9 papers, 2.7k citations indexed

About

Pengda Chen is a scholar working on Molecular Biology, Immunology and Cancer Research. According to data from OpenAlex, Pengda Chen has authored 9 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 3 papers in Immunology and 3 papers in Cancer Research. Recurrent topics in Pengda Chen's work include MicroRNA in disease regulation (3 papers), Circular RNAs in diseases (2 papers) and Cancer-related molecular mechanisms research (2 papers). Pengda Chen is often cited by papers focused on MicroRNA in disease regulation (3 papers), Circular RNAs in diseases (2 papers) and Cancer-related molecular mechanisms research (2 papers). Pengda Chen collaborates with scholars based in China, United States and Canada. Pengda Chen's co-authors include Jiahuai Han, Wanting He, Lichen Hu, Xin Wang, Zhang‐Hua Yang, Haoqiang Wan, Chuan‐Qi Zhong, Deli Huang, Xinru Zheng and Wenjuan Li and has published in prestigious journals such as Nature Communications, Cell Reports and Cancer Letters.

In The Last Decade

Pengda Chen

9 papers receiving 2.6k citations

Hit Papers

Gasdermin D is an executor of pyroptosis and required for... 2013 2026 2017 2021 2015 2013 500 1000 1.5k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Pengda Chen China 6 2.3k 926 339 277 189 9 2.7k
Lichen Hu China 5 2.3k 1.0× 897 1.0× 454 1.3× 226 0.8× 119 0.6× 6 2.6k
Sebastian Rühl Switzerland 9 2.4k 1.0× 1.1k 1.2× 411 1.2× 230 0.8× 94 0.5× 11 2.7k
Charles L. Evavold United States 12 1.7k 0.7× 888 1.0× 241 0.7× 196 0.7× 156 0.8× 17 2.2k
Pontus Ørning United States 13 1.5k 0.6× 738 0.8× 246 0.7× 240 0.9× 101 0.5× 16 1.9k
Yiting Tang China 24 1.2k 0.5× 787 0.8× 149 0.4× 313 1.1× 147 0.8× 50 2.1k
Dave Boucher Australia 17 2.5k 1.1× 1.3k 1.4× 376 1.1× 241 0.9× 51 0.3× 29 2.9k
Jeffrey J. Sadler United States 9 1.7k 0.7× 1.1k 1.2× 205 0.6× 327 1.2× 65 0.3× 9 2.5k
Christine A. Juliana United States 8 1.9k 0.8× 1.1k 1.2× 230 0.7× 212 0.8× 97 0.5× 14 2.2k
Laetitia Agostini Switzerland 5 2.2k 0.9× 1.5k 1.6× 248 0.7× 232 0.8× 86 0.5× 5 2.7k
Filip Van Hauwermeiren Belgium 23 1.8k 0.8× 1.1k 1.2× 119 0.4× 303 1.1× 339 1.8× 29 2.7k

Countries citing papers authored by Pengda Chen

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Pengda Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Pengda Chen. A scholar is included among the top collaborators of Pengda Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pengda Chen. Pengda Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Chen, Pengda, Li Yang, Liang Yang, et al.. (2025). A Csde1-Strap complex regulates plasma cell differentiation by coupling mRNA translation and decay. Nature Communications. 16(1). 2906–2906. 1 indexed citations
2.
Chen, Pengda, Mengdi Zhang, Nan Yao, et al.. (2024). Critical roles of the miR-17∼92 family in thymocyte development, leukemogenesis, and autoimmunity. Cell Reports. 43(6). 114261–114261. 4 indexed citations
3.
Du, Ying, Jun Xie, Pengda Chen, et al.. (2024). Critical and differential roles of eIF4A1 and eIF4A2 in B-cell development and function. Cellular and Molecular Immunology. 22(1). 40–53. 2 indexed citations
4.
He, Xiaoyu, Pengda Chen, Jun Xie, et al.. (2023). Dhx33 promotes B-cell growth and proliferation by controlling activation-induced rRNA upregulation. Cellular and Molecular Immunology. 20(3). 277–291. 7 indexed citations
5.
Sun, Mengmeng, et al.. (2020). Ascorbic Acid Promotes Plasma Cell Differentiation through Enhancing TET2/3-Mediated DNA Demethylation. Cell Reports. 33(9). 108452–108452. 35 indexed citations
6.
Yan, Zhifeng, Hongxia Zhang, Pengda Chen, & Wenxian Wang. (2017). Anisotropy of fatigue behavior and tensile behavior of 5A06 aluminum alloy based on infrared thermography. Journal of Wuhan University of Technology-Mater Sci Ed. 32(1). 155–161. 5 indexed citations
7.
Ma, Huabin, Jin‐Shui Pan, Lixin Jin, et al.. (2016). MicroRNA-17~92 inhibits colorectal cancer progression by targeting angiogenesis. Cancer Letters. 376(2). 293–302. 63 indexed citations
8.
He, Wanting, Haoqiang Wan, Lichen Hu, et al.. (2015). Gasdermin D is an executor of pyroptosis and required for interleukin-1β secretion. Cell Research. 25(12). 1285–1298. 1911 indexed citations breakdown →
9.
Chen, Xin, Wenjuan Li, Junming Ren, et al.. (2013). Translocation of mixed lineage kinase domain-like protein to plasma membrane leads to necrotic cell death. Cell Research. 24(1). 105–121. 624 indexed citations breakdown →

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.

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