Dongju Feng

884 total citations · 1 hit paper
17 papers, 651 citations indexed

About

Dongju Feng is a scholar working on Epidemiology, Molecular Biology and Immunology. According to data from OpenAlex, Dongju Feng has authored 17 papers receiving a total of 651 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Epidemiology, 8 papers in Molecular Biology and 6 papers in Immunology. Recurrent topics in Dongju Feng's work include Cytomegalovirus and herpesvirus research (7 papers), Herpesvirus Infections and Treatments (4 papers) and Epigenetics and DNA Methylation (2 papers). Dongju Feng is often cited by papers focused on Cytomegalovirus and herpesvirus research (7 papers), Herpesvirus Infections and Treatments (4 papers) and Epigenetics and DNA Methylation (2 papers). Dongju Feng collaborates with scholars based in China, United States and Vietnam. Dongju Feng's co-authors include Yun Chen, Hua Sun, Chupeng Hu, Yu Jin, Xiaoxin Mu, Jinying Lu, Feng Zhou, Changxian Li, Bin Gu and Xiaodong Wang and has published in prestigious journals such as Hepatology, Oncogene and Journal of Virology.

In The Last Decade

Dongju Feng

16 papers receiving 645 citations

Hit Papers

Gut microbiota–derived short‐chain fatty acids regulate g... 2022 2026 2023 2024 2022 40 80 120

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dongju Feng China 13 301 202 186 180 82 17 651
Xiaojun Li China 14 224 0.7× 88 0.4× 230 1.2× 144 0.8× 86 1.0× 43 734
Ian Gaël Rodrigue‐Gervais Canada 11 571 1.9× 104 0.5× 356 1.9× 199 1.1× 86 1.0× 13 880
Sharlene Velichko United States 16 228 0.8× 215 1.1× 403 2.2× 102 0.6× 77 0.9× 21 893
Peishuang Du United States 15 207 0.7× 214 1.1× 509 2.7× 178 1.0× 45 0.5× 18 942
Luigi Tortola Switzerland 14 328 1.1× 141 0.7× 612 3.3× 109 0.6× 53 0.6× 30 966
Keita Saeki Japan 11 250 0.8× 101 0.5× 192 1.0× 99 0.6× 30 0.4× 24 594
Xiaomin Yao China 12 540 1.8× 144 0.7× 308 1.7× 74 0.4× 67 0.8× 25 820
Arulkumaran Shanmugam United States 9 357 1.2× 126 0.6× 154 0.8× 59 0.3× 80 1.0× 14 659
Liping Tian China 12 278 0.9× 89 0.4× 494 2.7× 84 0.5× 134 1.6× 21 858
Paramananda Saikia United States 15 247 0.8× 71 0.4× 245 1.3× 368 2.0× 82 1.0× 20 884

Countries citing papers authored by Dongju Feng

Since Specialization
Citations

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

Fields of papers citing papers by Dongju Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dongju Feng

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

All Works

17 of 17 papers shown
1.
Hu, Zhaoyong, Wenjie Qu, Huili Yang, et al.. (2025). Genome-wide identification, expression analysis of the MYC gene family in Stevia rebaudiana and the functional identification of SrMYC8 in SGs biosynthesis. Industrial Crops and Products. 230. 121002–121002.
2.
Chen, Jinsong, Wenjie Qu, Kai Hou, et al.. (2024). Genome-wide identification of MYB genes and analysis of their expression under different abiotic stress conditions in Stevia rebaudiana. Industrial Crops and Products. 216. 118803–118803. 5 indexed citations
3.
Hu, Chupeng, Bingqing Xu, Xiaodong Wang, et al.. (2022). Gut microbiota–derived short‐chain fatty acids regulate group 3 innate lymphoid cells in HCC. Hepatology. 77(1). 48–64. 131 indexed citations breakdown →
4.
Liu, Boyuan, Zewei Zhou, Yu Jin, et al.. (2022). Hepatic stellate cell activation and senescence induced by intrahepatic microbiota disturbances drive progression of liver cirrhosis toward hepatocellular carcinoma. Journal for ImmunoTherapy of Cancer. 10(1). e003069–e003069. 75 indexed citations
5.
Xia, Qing, Jing Jia, Chupeng Hu, et al.. (2021). Tumor-associated macrophages promote PD-L1 expression in tumor cells by regulating PKM2 nuclear translocation in pancreatic ductal adenocarcinoma. Oncogene. 41(6). 865–877. 66 indexed citations
6.
Peng, Rui, Yan Chen, Gang Li, et al.. (2020). Resistance to FGFR1-targeted therapy leads to autophagy via TAK1/AMPK activation in gastric cancer. Gastric Cancer. 23(6). 988–1002. 21 indexed citations
7.
Yao, Yao, Zhongyi Yan, Chao Zhou, et al.. (2020). Prognostic value of novel immune-related genomic biomarkers identified in head and neck squamous cell carcinoma. Journal for ImmunoTherapy of Cancer. 8(2). e000444–e000444. 50 indexed citations
8.
Sun, Jie, Dongju Feng, Zewei Zhou, et al.. (2020). CD24 blunts the sensitivity of retinoblastoma to vincristine by modulating autophagy. Molecular Oncology. 14(8). 1740–1759. 31 indexed citations
9.
Feng, Dongju, Yao Yao, Peipei Li, et al.. (2019). Listeria-based hepatocellular carcinoma vaccine facilitates anti-PD-1 therapy by regulating macrophage polarization. Oncogene. 39(7). 1429–1444. 73 indexed citations
10.
Shao, Qing, Zhe Lin, Xiaohui Wu, et al.. (2016). Transcriptome sequencing of neurologic diseases associated genes in HHV-6A infected human astrocyte. Oncotarget. 7(30). 48070–48080. 9 indexed citations
11.
Li, Lingyun, Feng Zhou, Jing Chi, et al.. (2013). Cell cycle perturbations induced by human herpesvirus 6 infection and their effect on virus replication. Archives of Virology. 159(2). 365–370. 5 indexed citations
12.
Wang, Fang, Jing Chi, Guangyong Peng, et al.. (2013). Development of Virus-Specific CD4 + and CD8 + Regulatory T Cells Induced by Human Herpesvirus 6 Infection. Journal of Virology. 88(2). 1011–1024. 21 indexed citations
13.
Zhang, Guofeng, Feng Zhou, Bin Gu, et al.. (2012). In vitro and in vivo evaluation of ribavirin and pleconaril antiviral activity against enterovirus 71 infection. Archives of Virology. 157(4). 669–679. 75 indexed citations
14.
Chi, Jing, Fang Wang, Lingyun Li, et al.. (2011). The role of MAPK in CD4+ T cells toll-like receptor 9-mediated signaling following HHV-6 infection. Virology. 422(1). 92–98. 12 indexed citations
15.
Gu, Bin, Guofeng Zhang, Lingyun Li, et al.. (2011). Human herpesvirus 6A induces apoptosis of primary human fetal astrocytes via both caspase-dependent and -independent pathways. Virology Journal. 8(1). 530–530. 15 indexed citations
16.
Li, Lingyun, Bin Gu, Feng Zhou, et al.. (2011). Human Herpesvirus 6 Suppresses T Cell Proliferation through Induction of Cell Cycle Arrest in Infected Cells in the G 2 /M Phase. Journal of Virology. 85(13). 6774–6783. 37 indexed citations
17.
Wang, Fang, Kun Yao, Feng Zhou, et al.. (2006). Human Herpesvirus‐6‐Specific Interleukin 10‐Producing CD4+ T Cells Suppress the CD4+ T‐Cell Response in Infected Individuals. Microbiology and Immunology. 50(10). 787–803. 25 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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