Jing Ouyang

7.8k total citations · 3 hit papers
124 papers, 5.0k citations indexed

About

Jing Ouyang is a scholar working on Molecular Biology, Immunology and Infectious Diseases. According to data from OpenAlex, Jing Ouyang has authored 124 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Molecular Biology, 24 papers in Immunology and 19 papers in Infectious Diseases. Recurrent topics in Jing Ouyang's work include Lymphoma Diagnosis and Treatment (14 papers), Gut microbiota and health (14 papers) and Galectins and Cancer Biology (11 papers). Jing Ouyang is often cited by papers focused on Lymphoma Diagnosis and Treatment (14 papers), Gut microbiota and health (14 papers) and Galectins and Cancer Biology (11 papers). Jing Ouyang collaborates with scholars based in China, United States and Canada. Jing Ouyang's co-authors include Margaret A. Shipp, Scott J. Rodig, Przemysław Juszczyński, Donna Neuberg, Gabriel A. Rabinovich, Bjoern Chapuy, Evan A. O’Donnell, Michael R. Green, Papiya Sinha and Yaokai Chen and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nature Medicine.

In The Last Decade

Jing Ouyang

117 papers receiving 5.0k citations

Hit Papers

PD-L1 Expression Is Characteristic of a Subset of Aggress... 2007 2026 2013 2019 2013 2012 2007 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jing Ouyang China 35 1.9k 1.8k 1.6k 1.3k 371 124 5.0k
Soohyun Kim South Korea 44 3.4k 1.9× 1.6k 0.9× 2.5k 1.5× 391 0.3× 527 1.4× 151 7.2k
Qiang Pan‐Hammarström Sweden 48 3.2k 1.7× 793 0.4× 2.5k 1.6× 586 0.5× 313 0.8× 167 6.6k
Irma Joosten Netherlands 47 5.0k 2.7× 1.1k 0.6× 1.1k 0.7× 430 0.3× 320 0.9× 198 7.6k
Shigeru Fujita Japan 44 2.2k 1.2× 1.6k 0.9× 1.2k 0.7× 296 0.2× 415 1.1× 222 5.7k
Yan Zheng China 28 4.7k 2.5× 1.2k 0.7× 2.0k 1.3× 757 0.6× 506 1.4× 152 7.9k
Arnaldo Caruso Italy 39 1.5k 0.8× 1.3k 0.7× 1.4k 0.9× 406 0.3× 1.6k 4.2× 260 5.9k
Samuel Huber Germany 42 4.1k 2.2× 1.5k 0.9× 2.2k 1.4× 416 0.3× 545 1.5× 151 7.8k
Jay H. Bream United States 39 3.2k 1.7× 1.2k 0.6× 1.4k 0.8× 494 0.4× 800 2.2× 85 7.1k
Guido Ferlazzo Italy 47 6.6k 3.6× 2.1k 1.2× 1.2k 0.8× 330 0.3× 298 0.8× 135 8.4k
Peter Fritsch Austria 51 4.1k 2.2× 1.5k 0.8× 2.1k 1.3× 787 0.6× 372 1.0× 246 9.9k

Countries citing papers authored by Jing Ouyang

Since Specialization
Citations

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

Fields of papers citing papers by Jing Ouyang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jing Ouyang

This figure shows the co-authorship network connecting the top 25 collaborators of Jing Ouyang. A scholar is included among the top collaborators of Jing Ouyang 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 Jing Ouyang. Jing Ouyang 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.
Liu, Qin, et al.. (2025). YOLO-RDM: Innovative Detection Methods for Eggplants and Stems in Complex Natural Environment. IEEE Access. 13. 37656–37672. 2 indexed citations
3.
Fan, Jun, et al.. (2023). The inhibition of FTO attenuates the antifibrotic effect of leonurine in rat cardiac fibroblasts. Biochemical and Biophysical Research Communications. 693. 149375–149375. 8 indexed citations
4.
Xia, Chao, Xue Zhang, Vijay Harypursat, Jing Ouyang, & Yaokai Chen. (2023). The role of pyroptosis in incomplete immune reconstitution among people living with HIV:Potential therapeutic targets. Pharmacological Research. 197. 106969–106969. 6 indexed citations
7.
Ouyang, Jing, et al.. (2022). Genomic signatures reveal selection in Lingxian white goose. Poultry Science. 102(1). 102269–102269. 10 indexed citations
8.
Chen, Hao, Min Huang, Hongbo Tang, et al.. (2022). Genomic signatures and evolutionary history of the endangered blue-crowned laughingthrush and other Garrulax species. BMC Biology. 20(1). 188–188. 2 indexed citations
9.
Ouyang, Jing, et al.. (2022). Microbiota-Meditated Immunity Abnormalities Facilitate Hepatitis B Virus Co-Infection in People Living With HIV: A Review. Frontiers in Immunology. 12. 755890–755890. 12 indexed citations
10.
Guo, Kun, et al.. (2021). The negative mental health condition among different occupational group in shaanxi province of china during the covid-19 pandemic. Annals of the Romanian Society for Cell Biology. 25(1). 2561–2564. 1 indexed citations
11.
Cader, Fathima Zumla, Xihao Hu, Walter L. Goh, et al.. (2020). A peripheral immune signature of responsiveness to PD-1 blockade in patients with classical Hodgkin lymphoma. Nature Medicine. 26(9). 1468–1479. 88 indexed citations
12.
Lin, John, Jing Ouyang, Xiaorong Peng, et al.. (2020). Potential therapeutic options for COVID-19: using knowledge of past outbreaks to guide future treatment. Chinese Medical Journal. 133. 1 indexed citations
13.
Zang, Shuang, et al.. (2020). Interpretation of China’s 2017 health expenditure: a latent profile analysis of panel data. BMJ Open. 10(6). e035512–e035512. 3 indexed citations
14.
Li, Haiyu, et al.. (2020). A Novel lncRNA, AK130181, Contributes to HIV-1 Latency by Regulating Viral Promoter-Driven Gene Expression in Primary CD4+ T Cells. Molecular Therapy — Nucleic Acids. 20. 754–763. 18 indexed citations
15.
Cader, Fathima Zumla, Ron C.J. Schackmann, Xihao Hu, et al.. (2018). Mass cytometry of Hodgkin lymphoma reveals a CD4+ regulatory T-cell–rich and exhausted T-effector microenvironment. Blood. 132(8). 825–836. 111 indexed citations
16.
Wu, Xinqi, Jingjing Li, Xiaoyun Liao, et al.. (2017). Combined Anti-VEGF and Anti–CTLA-4 Therapy Elicits Humoral Immunity to Galectin-1 Which Is Associated with Favorable Clinical Outcomes. Cancer Immunology Research. 5(6). 446–454. 58 indexed citations
17.
Liu, Yao, Jun Lv, Bo Yang, et al.. (2015). Lycium barbarum polysaccharide attenuates type II collagen-induced arthritis in mice. International Journal of Biological Macromolecules. 78. 318–323. 29 indexed citations
18.
Chen, Benjamin J., Bjoern Chapuy, Jing Ouyang, et al.. (2013). PD-L1 Expression Is Characteristic of a Subset of Aggressive B-cell Lymphomas and Virus-Associated Malignancies. Clinical Cancer Research. 19(13). 3462–3473. 657 indexed citations breakdown →
19.
Green, Michael R., Scott J. Rodig, Przemysław Juszczyński, et al.. (2012). Constitutive AP-1 Activity and EBV Infection Induce PD-L1 in Hodgkin Lymphomas and Posttransplant Lymphoproliferative Disorders: Implications for Targeted Therapy. Clinical Cancer Research. 18(6). 1611–1618. 551 indexed citations breakdown →
20.
Juszczyński, Przemysław, Scott J. Rodig, Jing Ouyang, et al.. (2010). MLL -Rearranged B Lymphoblastic Leukemias Selectively Express the Immunoregulatory Carbohydrate-Binding Protein Galectin-1. Clinical Cancer Research. 16(7). 2122–2130. 28 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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