Chaowen Shi

462 total citations
11 papers, 355 citations indexed

About

Chaowen Shi is a scholar working on Pulmonary and Respiratory Medicine, Molecular Biology and Genetics. According to data from OpenAlex, Chaowen Shi has authored 11 papers receiving a total of 355 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Pulmonary and Respiratory Medicine, 6 papers in Molecular Biology and 2 papers in Genetics. Recurrent topics in Chaowen Shi's work include Neonatal Respiratory Health Research (6 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (5 papers) and Mesenchymal stem cell research (2 papers). Chaowen Shi is often cited by papers focused on Neonatal Respiratory Health Research (6 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (5 papers) and Mesenchymal stem cell research (2 papers). Chaowen Shi collaborates with scholars based in China, United States and Sweden. Chaowen Shi's co-authors include Xiaodong Han, Zou Xiang, Zhaorui Sun, Kebin Hu, Xiang Chen, Honghui Cao, Weiping Qian, Xiang Chen, Jiwei Hou and Ling Chen and has published in prestigious journals such as Journal of Biological Chemistry, Biomaterials and Scientific Reports.

In The Last Decade

Chaowen Shi

11 papers receiving 348 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chaowen Shi China 10 166 150 51 44 42 11 355
Daniel H. Y. Shen Taiwan 11 98 0.6× 152 1.0× 50 1.0× 27 0.6× 100 2.4× 19 498
Rekha Chaudhary United States 8 79 0.5× 88 0.6× 78 1.5× 53 1.2× 23 0.5× 27 283
Jeffrey A. Meridew United States 10 255 1.5× 149 1.0× 22 0.4× 26 0.6× 41 1.0× 20 425
Valérie Rimelen France 6 83 0.5× 134 0.9× 69 1.4× 36 0.8× 37 0.9× 10 252
Hanru Ren China 13 90 0.5× 137 0.9× 31 0.6× 50 1.1× 95 2.3× 29 400
Agnes Banfalvi United States 6 302 1.8× 161 1.1× 28 0.5× 28 0.6× 85 2.0× 7 482
Esha Singh United Kingdom 8 80 0.5× 145 1.0× 47 0.9× 27 0.6× 53 1.3× 17 282
Yongheng Gao China 11 92 0.6× 239 1.6× 31 0.6× 134 3.0× 28 0.7× 21 386
Chengen Wang China 8 100 0.6× 92 0.6× 73 1.4× 28 0.6× 79 1.9× 17 291
John Floyd United States 12 76 0.5× 55 0.4× 89 1.7× 47 1.1× 38 0.9× 39 307

Countries citing papers authored by Chaowen Shi

Since Specialization
Citations

This map shows the geographic impact of Chaowen Shi'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 Chaowen Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chaowen Shi more than expected).

Fields of papers citing papers by Chaowen Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chaowen Shi. 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 Chaowen Shi. The network helps show where Chaowen Shi may publish in the future.

Co-authorship network of co-authors of Chaowen Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Chaowen Shi. A scholar is included among the top collaborators of Chaowen Shi 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 Chaowen Shi. Chaowen Shi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
2.
Lin, Ling, Chaowen Shi, Zhaorui Sun, et al.. (2019). The Ser/Thr kinase p90RSK promotes kidney fibrosis by modulating fibroblast–epithelial crosstalk. Journal of Biological Chemistry. 294(25). 9901–9910. 11 indexed citations
3.
Wang, Cong, et al.. (2019). Expression analysis of microRNAs and mRNAs in myofibroblast differentiation of lung resident mesenchymal stem cells. Differentiation. 112. 10–16. 13 indexed citations
4.
Chen, Xiang, Chaowen Shi, Honghui Cao, et al.. (2018). The hedgehog and Wnt/β-catenin system machinery mediate myofibroblast differentiation of LR-MSCs in pulmonary fibrogenesis. Cell Death and Disease. 9(6). 639–639. 63 indexed citations
5.
Chen, Xiang, Chaowen Shi, Weilin Liu, et al.. (2017). The role of miR-497-5p in myofibroblast differentiation of LR-MSCs and pulmonary fibrogenesis. Scientific Reports. 7(1). 40958–40958. 41 indexed citations
6.
Cao, Xiaowei, Xiang Chen, Chaowen Shi, et al.. (2016). Process characterization of epithelial–mesenchymal transition in alveolar epithelial type II cells using surface-enhanced Raman scattering spectroscopy. RSC Advances. 6(17). 14321–14328. 7 indexed citations
7.
Chen, Xiang, Chaowen Shi, Xiannan Meng, et al.. (2016). Inhibition of Wnt/β-catenin signaling suppresses bleomycin-induced pulmonary fibrosis by attenuating the expression of TGF-β1 and FGF-2. Experimental and Molecular Pathology. 101(1). 22–30. 58 indexed citations
9.
Sun, Zhaorui, Chaowen Shi, Fangfang Sun, et al.. (2014). Activated Wnt signaling induces myofibroblast differentiation of mesenchymal stem cells, contributing to pulmonary fibrosis. International Journal of Molecular Medicine. 33(5). 1097–1109. 52 indexed citations
10.
Shi, Chaowen, et al.. (2014). Role of Wnt/β‐Catenin Signaling in Epithelial Differentiation of Lung Resident Mesenchymal Stem Cells. Journal of Cellular Biochemistry. 116(8). 1532–1539. 32 indexed citations
11.
Wang, Cong, Jinghong Dai, Zhaorui Sun, et al.. (2014). Targeted inhibition of disheveled PDZ domain via NSC668036 depresses fibrotic process. Experimental Cell Research. 331(1). 115–122. 39 indexed citations

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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