Jiang Ren

1.9k total citations · 2 hit papers
34 papers, 1.3k citations indexed

About

Jiang Ren is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Jiang Ren has authored 34 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 14 papers in Oncology and 6 papers in Immunology. Recurrent topics in Jiang Ren's work include TGF-β signaling in diseases (8 papers), Cancer Cells and Metastasis (8 papers) and RNA Interference and Gene Delivery (6 papers). Jiang Ren is often cited by papers focused on TGF-β signaling in diseases (8 papers), Cancer Cells and Metastasis (8 papers) and RNA Interference and Gene Delivery (6 papers). Jiang Ren collaborates with scholars based in China, Netherlands and Sweden. Jiang Ren's co-authors include Peter ten Dijke, Sijia Liu, Long Zhang, Fangfang Zhou, Hans van Dam, Zhi Zong, Josephine Iaria, Yujun Wei, Hong‐Jian Zhu and Wen Zhu and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Jiang Ren

33 papers receiving 1.3k citations

Hit Papers

Targeting TGFβ signal transduction for cancer therapy 2021 2026 2022 2024 2021 2025 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jiang Ren China 21 772 499 289 212 130 34 1.3k
Jenny G. Parvani United States 15 712 0.9× 587 1.2× 257 0.9× 175 0.8× 106 0.8× 19 1.2k
Prerna Suri India 8 1.1k 1.4× 852 1.7× 282 1.0× 238 1.1× 105 0.8× 9 1.6k
Damian J. Junk United States 17 777 1.0× 695 1.4× 341 1.2× 320 1.5× 100 0.8× 27 1.4k
Alison M. Karst United States 18 927 1.2× 578 1.2× 407 1.4× 200 0.9× 150 1.2× 21 1.8k
Francesca Di Modugno Italy 20 681 0.9× 519 1.0× 284 1.0× 234 1.1× 107 0.8× 43 1.3k
Sachi Horibata United States 16 838 1.1× 477 1.0× 281 1.0× 550 2.6× 123 0.9× 31 1.6k
Shilpee Dutt India 21 902 1.2× 295 0.6× 199 0.7× 269 1.3× 74 0.6× 48 1.5k
Meike de Wit Netherlands 21 666 0.9× 408 0.8× 295 1.0× 92 0.4× 205 1.6× 43 1.2k
Viswanathan Muthusamy United States 17 996 1.3× 483 1.0× 208 0.7× 273 1.3× 64 0.5× 28 1.4k

Countries citing papers authored by Jiang Ren

Since Specialization
Citations

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

Fields of papers citing papers by Jiang Ren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiang Ren

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

All Works

20 of 20 papers shown
1.
Zong, Zhi, Jiang Ren, Bing Yang, Long Zhang, & Fangfang Zhou. (2025). Emerging roles of lysine lactyltransferases and lactylation. Nature Cell Biology. 27(4). 563–574. 20 indexed citations breakdown →
2.
Ren, Jiang, et al.. (2024). TGFβ family signaling in human stem cell self-renewal and differentiation. Cell Regeneration. 13(1). 26–26. 3 indexed citations
3.
Ren, Jiang, et al.. (2024). Inhibitor of differentiation 3 confers the robust anti‐tumor activity of Kupffer cells. SHILAP Revista de lepidopterología. 5(9). e708–e708.
4.
Ren, Jiang, Peng Yu, Sijia Liu, et al.. (2023). Deubiquitylating Enzymes in Cancer and Immunity. Advanced Science. 10(36). e2303807–e2303807. 49 indexed citations
5.
Ren, Jiang, et al.. (2023). Ras homolog family member J (RHOJ): a key regulator of chemoresistance associated with epithelial-mesenchymal transition. Signal Transduction and Targeted Therapy. 8(1). 376–376. 2 indexed citations
6.
Okita, Yukari, Shady Younis, Jens Eriksson, et al.. (2022). TGFβ selects for pro‐stemness over pro‐invasive phenotypes during cancer cell epithelial–mesenchymal transition. Molecular Oncology. 16(12). 2330–2354. 9 indexed citations
7.
Li, Chao, Jin Ma, Arwin Groenewoud, et al.. (2022). Establishment of Embryonic Zebrafish Xenograft Assays to Investigate TGF-β Family Signaling in Human Breast Cancer Progression. Methods in molecular biology. 2488. 67–80. 5 indexed citations
8.
Ren, Jiang, Midory Thorikay, Maarten van Dinther, et al.. (2021). Inhibiting Endothelial Cell Function in Normal and Tumor Angiogenesis Using BMP Type I Receptor Macrocyclic Kinase Inhibitors. Cancers. 13(12). 2951–2951. 5 indexed citations
9.
Liu, Sijia, Jiang Ren, & Peter ten Dijke. (2021). Targeting TGFβ signal transduction for cancer therapy. Signal Transduction and Targeted Therapy. 6(1). 8–8. 261 indexed citations breakdown →
10.
Zong, Zhi, Yujun Wei, Jiang Ren, Long Zhang, & Fangfang Zhou. (2021). The intersection of COVID-19 and cancer: signaling pathways and treatment implications. Molecular Cancer. 20(1). 76–76. 45 indexed citations
12.
Almaas, Eivind, Jiang Ren, Sen Zhao, et al.. (2019). GREM1 is associated with metastasis and predicts poor prognosis in ER-negative breast cancer patients. Cell Communication and Signaling. 17(1). 140–140. 39 indexed citations
13.
Ren, Jiang, Marcel Smid, Josephine Iaria, et al.. (2019). Cancer-associated fibroblast-derived Gremlin 1 promotes breast cancer progression. Breast Cancer Research. 21(1). 109–109. 119 indexed citations
14.
Ren, Jiang, et al.. (2017). Invasive Behavior of Human Breast Cancer Cells in Embryonic Zebrafish. Journal of Visualized Experiments. 36 indexed citations
15.
Wang, Yu, Weihan Yang, Qiang Pu, et al.. (2015). The effects and mechanisms of SLC34A2 in tumorigenesis and progression of human non-small cell lung cancer. Journal of Biomedical Science. 22(1). 52–52. 34 indexed citations
16.
Yang, Weihan, Yu Wang, Qiang Pu, et al.. (2014). Elevated expression of SLC34A2 inhibits the viability and invasion of A549 cells. Molecular Medicine Reports. 10(3). 1205–1214. 19 indexed citations
17.
Ma, Qingping, Qianqian Jiang, Qiang Pu, et al.. (2013). MicroRNA-143 Inhibits Migration and Invasion of Human Non-Small-Cell Lung Cancer and Its Relative Mechanism. International Journal of Biological Sciences. 9(7). 680–692. 58 indexed citations
18.
Ren, Jiang, et al.. (2012). Cationic Lipids Containing Cyclen and Ammonium Moieties as Gene Delivery Vectors. Chemical Biology & Drug Design. 79(6). 879–887. 12 indexed citations
19.
Yang, Weihan, Yu Wang, Qingping Ma, et al.. (2012). Cationic liposome-mediated nitric oxide synthase gene therapy enhances the antitumor effects of cisplatin in lung cancer. International Journal of Molecular Medicine. 31(1). 33–42. 18 indexed citations
20.
Zhang, Yang, Jiang Ren, Yun Fu, et al.. (2011). Cyclen-Based Cationic Lipids for Highly Efficient Gene Delivery towards Tumor Cells. PLoS ONE. 6(8). e23134–e23134. 27 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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